Sign PDF for Legal Mobile

Legal mobile refers to the ability to manage and execute legal documents on mobile devices. airSlate SignNow offers a seamless legal mobile solution that allows users to send, eSign, and manage documents directly from their smartphones or tablets, ensuring efficiency and flexibility in legal processes.

The pricing for legal mobile users is competitive and varies based on the plan you choose. airSlate SignNow offers flexible pricing options that cater to businesses of all sizes, ensuring you get a cost-effective solution for your legal mobile documentation needs.

airSlate SignNow provides advanced features such as document templates, mobile signing, and automated workflows designed specifically for legal mobile use. These features make it easy to create, send, and track legal documents on the go, enhancing productivity.

Absolutely! Security is a top priority for airSlate SignNow. The platform provides end-to-end encryption, secure cloud storage, and compliance with legal standards, ensuring that your legal mobile documents are protected at all times.

Yes, airSlate SignNow offers seamless integrations with various legal software and applications. This capability enhances your legal mobile experience by allowing you to connect tools you already use, streamlining your workflow and improving efficiency.

Using airSlate SignNow for legal mobile documentation provides numerous benefits including time savings, reduced paper usage, and the convenience of signing documents from anywhere. The platform enhances collaboration while ensuring that all legal mobile processes are easy to manage.

airSlate SignNow provides exceptional customer support for all users, including those using the legal mobile functionality. You can access help through various channels such as live chat, email support, and an extensive knowledge base to resolve any issues you may face.

Software I’d recommend checking out is Document 365 Business - if you’re a small legal practice, you still deal with a lot of documents that need to be organized and saved in the cloud for easy access and peace of mind. Document 365 performs well in this particular category - when you create a team shared account, all your documents are synced and this makes for easy collaboration for small and large teams both. If you’re a licensed member, you get 1TB of cloud space and you can share documents with colleagues with password protected links. Working with PDFs is also easy with the PDF mobile reader app - editing and signing, as well as annotating and highlighting, all to increase your productivity and decrease your workload. Collaborating on file editing, file transfer and sharingPDF conversions or turning any paper documents to editable text with OCR,  Access from anywhere and from any device, security of your files with passwords and watermarks Send out files quickly and efficiently to clients - either through email or by faxingManage your team and team projects, edit agreements and contracts - quickly and on the go.  Disclaimer: I am part of Kdan’s team and my answers might be a bit biased.

What is Digital Signature?A digital signature is basically a way to ensure that an electronic document (e-mail, spreadsheet, text file, etc.) is authentic. Authentic means that you know who created the document and you know that it has not been altered in any way since that person created it.Digital signatures rely on certain types of encryption to ensure authentication. Encryption is the process of taking all the data that one computer is sending to another and encoding it into a form that only the other computer will be able to decode. Authentication is the process of verifying that infor...

I am working on an ML project, in which I predict the performance of the Indian Cricket Team at the World Cup 2015.For this, I have been crawling data from some top cricket sites like cricbuzz, cricinfo, etc. Then, the data is analyzed and the type of batsman, bowler, pitch, position of batting/bowling, venue, opposition, etc are taken as predictors.In this analysis, the best team composition against a particular opposition, venue, the strengths and weaknesses of the opposition team is also determined, by selecting the best pool of players.Ex: Rohit and Dhawan would be the best opening pair on sub-continent like pitches,but would they be as effective if the opposition is Sri Lanka?I've written the scraper in Python, and planning to  use multi-layered neural networks (or deep learning) for the problem. I would really love to have collaborators in this project.

There are quite a few alternate software out there that can help you in case you don’t want to work with signNow. Given below is a list of options you could try your hand at.#1. iSkysoft PDF Editor Pro (Mac and Windows)As a suitable alternative to signNow, you can download iSkysoft PDF Editor Pro for Mac and iSkysoft PDF Editor for Windows. This software comes with the facility of letting you edit your PDF documents in a broad scope as it is done in Office Word processor. It also lets you convert PDF documents to Word documents, Excel, HTML, PPT, EPUB, Images and more. And more features are available:Edit native and scanned PDF by adding, deleting or changing texts, images, and others in PDF.Annotate or mark up PDF with text boxes, sticky notes or freehand drawings.Convert standard and scanned PDF to Word, PPT, Excel, Images, HTML, and other formats.Create PDF from existing PDF, Webpages, HTML, and Text files.Quickly sign PDF and make comments. Decrypt or encrypt PDFs.Combine, compress or split PDF documents.Fill out PDF and create PDF from many free PDF form templates. #2. Nitro Pro 9 (Windows)Nitro Pro 9 is another signNow alternative that is gaining popularity when it comes to handling documents. The software comes with integrated Internet cloud facilities. It helps users to make new documents, edit them and share them with others easily both offline and online.Price: $ 183.58Pros:The documents created on Nitro Pro are PDF documents that can be opened from any PDF reader, and on any mobile device too.The Nitro Cloud feature lets users sign and share documents with users of different browsers.Cons:Nitro Pro 9 provides no facility for PDF indexing.It OCR facility malfunctions when it comes to big-sized documents. #3. Foxit PDF Editor (Windows)Foxit PDF Editor is a smooth-working PDF editing program. When it comes to PDF editing Foxit’s facilities match that of word processing software. This PDF editor locates test boxes automatically and lets users edit paragraphs within the text boxes.Price: $ 99Pros:It allows users to split or join text blocks to edit easily, where users can resize or move text blocks to get a definite layout.Its image editing capabilities are also better incorporated.Cons:It comes with a detached plug-in facility that needs to be installed separately.The process to update the plug-in is not clear. #4. signNow (Mac, Windows, Linux)signNow is a user-friendly signNow alternative that comes at half the price of signNow. It includes all the editing and extra features that a good PDF editing system has, while being in compliance with the PDF document standards.Price: $ 89Pros:It can annotate PDF documents, besides being able to make PDFs out of Word documents, images and other texts.It includes document support in the form of Google Drive SharePoint.Cons:Its trial version cones with a watermark.There is no provision of ‘Undo’, besides, it also doesn’t work with common trackpad commands like shrink or zoom. #5. signNow (Mac)signNow is a PDF editing software that is compatible with the Mac OS, and has the added advantage of reasonably priced. It has the common features of a PDF editor like making changes or correcting typos in the main text document, besides it also lets users add texts, signatures and images.Price: $ 59.95Pros:It has the ability to export Ms-Word files to the PDF format.It can scan images with OCR and turn it into a text document.Cons:It has some functional issues like pages can occasionally seem out of focus. Long documents take longer time to load.It also does not have features like Page Labelling. #6. PDFClerk Pro (Mac)PDFClerk Pro is a software known for its high-speed functionality when it comes to handling PDF documents. It comes with various interesting features where you can also make a PDF document in other foreign languages where it can be read from right to left as in Hebrew or Arabic. It gives you more layout options than most other softwares.Price: $ 48.00Pros:Letting users resize pages or even entire documents to another page size, and also letting them shift the content of the pages if necessary.Permitting users to export single pages in the bitmap (png, jpg etc.) format, or even make audio files from a text’s document.Cons:Page mark-up tools are absent.Visually the interface is not quite appealing. #7. PDF Signet (Mac)PDF signet is a Mac signNow alternative. It lets its users sign PDF documents with a X.509 certificate in a user-friendly manner. The app also lets users verify signatures by simply dropping the concerned PDF file into the app.Price: $ 10Pros:It allows users to place their signatures digitally on PDF files through any device.The certificate for signing can be employed easily from the Keychain.It also automatically signs documents as you make them.It also confirms the validity of existing signatures.Cons:Limited to a certain area of functionality in PDF documents.It is only compatible on the OS X 10.7 or later versions of the system.#8. Infix PDF Editor (Mac and Windows)Infix PDF Editor is an signNow alternative that edits PDF files in the manner of a word-processing software. Hence it is simple and highly functional when it comes to reformatting edited documents. From altering texts, font sizes and images, reutilizing and editing PDF files without needing the source file to filling in forms Infix PDF Editor is a resourceful software.Price: $ 99Pros:Its software akin to that of a word-processor makes it really easy to use, sans any complex functions.It can copy text and images between PDF files.It has the feature to Search and replace, not only in individual files but across multiple files simultaneously.Cons:When filling forms users will find a watermark appearing on the final document.Quite a few features are missing in its Standard and Advanced mode. #9. deskPDF Creator (Mac and Windows)Powered by Docudesk, deskPDF gives users the facility to convert documents of any format to PDF files. Compatible with both the Mac and Windows operating systems, this software contains easy-to-use but signNow features like a drag-and-drop option to convert files to the PDF format, besides watermarking, merging, PDF file security provisions and custom profile workflows.Price:$ 34.95Pros:It comes installed with a virtual printer that assists in converting any file that has the ‘Print’ option to the PDF format.The PDF Preview feature facilitates users to view the file before it is printed, and even lets them rotate or remove pages if they require to.A swifter PDF creation engine ensures greater facilities. Users can select between making PDFs in quality formats or optimized small-sized PDFs that can be shared online or through emails.Cons:A nag screen that disturbs users in the trial version.Complicated advanced features that users take time to understand. #10. Proview (Mac)Compatible with the Mac OS X, Proview is a PDF editor that employs a broad array of features to edit documents and also to create new PDF documents. With this software users can remove or add PDF files, or make changes to multiple parts of a PDF text. All its features are quick and easy to execute.Price: $ 42.26Pros:Comprehensive and interactive tools, with greater formatting features that includes transparency as well.The tools of Trim, Bleed and art boxes, besides the capability of labelling multiple pages together.Cons:The fact that the documents edited by it trial version carry the watermark of ‘Demo’ across it.Its inadequate features as compared to Acrobat X Pro. #11.DigsignNower (free, Mac, Windows, Linux)DigsignNower is a free alternative to signNow that is compatible with Mac, Windows and also the Linux operating system, and is used to see PDF files and create digital signatures on them employing the X.509 certificates. The application is capable of endorsing and handling complicated functions like multiple signing of documents, USB sticks, smart cards and key stores.Price: FreePros:Its user-friendly interface, which can be either employed as a web device or an installed program.The facility to let users make legally validated signatures on PDF documents for free, utilizing the X.509 certificate.Cons:Its small area of specialization where it yields restricted features on the particular aspect of signing documents.The free edition is subject to only essential tools, whereas the paid application comes with greater facilities of time stamp, Smartcard/USB tokens, server support besides one year email assistance. #12. PDFLab (free, Mac)PDFLab is another free signNow alternative for Mac that permits users to divide and merge PDF files, besides letting them add images as well as blank pages. It also gives users the ease to build PDF documents by joining multiple images. Using it can be simple, as users only need to insert their files in a list, pick the pages, arrange them in a sequence and build a new PDF file.Price: FreePros:It comes with functions that let users swiftly divide a document into multiple ones.It also lets users password-protect files or decrypt them according to their needs.Cons:It is only compatible with a Mac OS.It comes with limited features as compared to a full-blown PDF editor. #13. Master PDF Editor (free, Mac, Windows, Linux)The Master PDF Editor is a free alternative to signNow that handles PDF and XPS files well. Though there is a paid edition the demo edition also lets users access all its features that include editing PDF files with both images and texts. Users can also build XPS or PDF files besides converting files between the two formats.Price:$ 49.95Pros:Users can edit or insert bookmarks in PDF documents, as well as encrypt them employing the 128 bit encryption method.Inserting PDF control tools like buttons, lists, checkboxes into the PDF files.Cons:The lack of a drag-and-drop tool.The trial version has a watermark that is added to all edited PDF files. #14. FreePDF (free, Windows)FreePDF is a free alternative to signNow for Windows that is generally used for seeing PDF files. FreePDF assists users in filling, signing and sending forms via email quickly. Its PDF viewer system is also integrated with features like page rotation, page snapshot, multi view mode etc. and lets users easily navigate through the PDF documents while making edits.Price: FreePros:The text overlay tool that facilitates users to insert a text overlay in their PDF files, as well as the signature overlay tool.It has improved form-filling tools in the form of the filling radio buttons.Cons:To some users it has inadequate PDF editing features when it comes to professional work.It is only compatible with the Windows OS. #15. PrimoPDF (free, Windows)PrimoPDF is a PDF building application that works smoothly with the Windows operating system. The PDF creation tool is rather quick and easy with the drag and drop feature that creates perfectly standardized PDF documents. Being free makes this software doubly popular for people to choose this as the ultimate PDF creation application.Price: FreePros:It gives users the capability to password-protect files and design definite particulars to precisely edit files.File conversion of files of different formats is just as simple with no reduction in quality with PrimoPDF.Cons:The user support links are often broken, and provide inconsistent support.The design of the software is simplistic and riddled with advertisements for other software.

Below is the List of Distinguished Final Year 100+ Machine Learning Projects Ideas or suggestions for Final Year students you can complete any of them or expand them into longer projects if you enjoy them.Nonlinear Reconstruction of Genetic Networks Implicated in AML.Aaron Goebel, Mihir Mongia .[pdf]Can Machines Learn Genres.Aaron Kravitz, Eliza Lupone, Ryan Diaz.[pdf]Identifying Gender From Facial Features.Abhimanyu Bannerjee, Asha Chigurupati.[pdf]Equation to LaTeX.Abhinav Rastogi, Sevy Harris.[pdf]Intensity prediction using DYFI.Abhineet Gupta.[pdf]Artificial Intelligence on the Final Frontier – Using Machine Learning to Find New Earths.Abraham Botros.[pdf]Life Expectancy Post Thoracic Surgery.Adam Abdulhamid, Ivaylo Bahtchevanov, Peng Jia.[pdf]Making Sense of the Mayhem- Machine Learning and March Madness.Adam Ginzberg, Alex Tran.[pdf]Better Reading Levels through Machine Learning.AdamGall.[pdf]What are People Saying about Net Neutrality.Adison Wongkar, Christoph Wertz.[pdf]Bird Species Identification from an Image.Aditya Bhandari, Ameya Joshi, Rohit Patki.[pdf]Stay Alert.Aditya Sarkar, Quentin Perrot, Julien Kawawa.[pdf]A bigram extension to word vector representation.Adrian Sanborn, Jacek Skryzalin.[pdf]Mining for Confusion – Classifying Affect in MOOC Learners’ Discussion Forum Posts.Akshay Agrawal, Shane Leonard.[pdf]Cardiac Arrhythmias Patients.AlGharbi Fatema, Fazel Azar, Haider Batool.[pdf]Prediction of Average and Perceived Polarity in Online Journalism.Albert Chu, Kensen Shi, Catherine Wong.[pdf]Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks.Albert Haque.[pdf]Nicolas Sanchez Ruck Those Stats!.Alejandro Sanchez.[pdf]Classifying Wikipedia People Into Occupations.Aleksandar Gabrovski.[pdf]Classification of Soil Contamination.Aleo Mok.[pdf]Automated Essay Grading.Alex Adamson, Andrew Lamb, Ralph Ma.[pdf]Relative and absolute equity return prediction using supervised learning.Alex Alifimoff, Axel Sly.[pdf]Seizure Prediction from Intracranial EEG Recordings.Alex Fu, Spencer Gibbs, Yuqi Liu.[pdf]Predicting Seizure Onset with Intracranial Electroencephalogram(EEG) Data.Alex Greaves, Arushi Raghuvanshi, Kai-Yuan Neo.[pdf]Classifying Complex Legal Documents.Alex Ratner.[pdf]Machine Learning Applied to the Detection of Retinal Blood Vessels.Alex Yee.[pdf]Survival Outcome Prediction for Cancer Patients.Alexander Herrmann .[pdf]Predicting Cellular Link Failures to Improve User Experience on Smartphones.Alexander Tom, Srini Vasudevan.[pdf]Yelp Personalized Reviews.Alexis Weill, Thomas Palomares, Arnaud Guille.[pdf]KMeansSL.Alfred Xue, Colin Wei.[pdf]Strength in numbers_ Modelling the impact of businesses on each other.Amir Sadeghian, Hakan Inan, Andres Noetzli.[pdf]Correlation Based Multi-Label Classification.Amit Garg, Jonathan Noyola, Romil Verma.[pdf]Landmark Recognition Using Machine Learning.Andrew Crudge, Will Thomas, Kaiyuan Zhu.[pdf]CarveML an application of machine learning to file fragment classification.Andrew Duffy.[pdf]rClassifier.Andrew Giel,Jon NeCamp,HussainKader.[pdf]Using Vector Representations to Augment Sentiment Analysis Training Data.Andrew McLeod, Lucas Peeters.[pdf]What Project Should I Choose.Andrew Poon.[pdf]Analyzing Vocal Patterns to Determine Emotion.Andy Sun, Maisy Wieman.[pdf]Predicting the Commercial Success of Songs Based on Lyrics and Other Metrics.Angela Xue, Nick Dupoux.[pdf]Application Of Machine Learning To Aircraft Conceptual Design.Anil Variyar.[pdf]Extracting Word Relationships from Unstructured Data.Anirudha Bhat, Krithika Iyer, Rahul Venkatraj.[pdf]Machine Learning for Predicting Delayed Onset Trauma Following Ischemic Stroke.Anthony Ma, Gus Liu.[pdf]Classifying Online User Behavior Using Contextual Data.Anunay Kulshrestha, Akshay Rampuria, Aditya Ramakrishnan.[pdf]Real Time Flight Path Optimization Under Constraints Using Surrogate Flutter Function.Arthur Paul-Dubois-Taine.[pdf]Real-Time Dense Map Matching with Naive Hidden Markov Models Delay versus Accuracy.Arun Jambulapati, Juhana Kangaspunta, Youssef Ahres, Loek Janssen.[pdf]Prediction Function from Sequence in Venom Peptide Families.Arvind Kannan, G. Seshadri.[pdf]Restaurant Recommendation System.Ashish Gandhe.[pdf]Home Electricity Load Forecasting.Atinuke Ademola Idowu, Pawel Kupsc, Sonya Mollinger.[pdf]Learning Dota 2 Team Compositions.Atish Agarwala, Michael Pearce.[pdf]Applying Deep Learning to derive insights about non-coding regions of the genome.Avanti Shrikumar, Anna Saplitski, Sofia Luna Frank-Fischer.[pdf]Classification of Higgs Jets as Decay Products of a Randall-Sundrum Graviton at the ATLAS Experiment.Aviv Cukierman, Zihao Jiang.[pdf]SemenFertilityPrediction.Axel Guyon,Florence Koskas,Yoann Buratti.[pdf]Sentiment Analysis Using Semi-Supervised Recursive Autoencoders and Support Vector Machines.Bahareh Ghiyasian, Yun Fei Guo.[pdf]Classifying Syllables in Imagined Speech using EEG Data.Barak Oshri, Nishith Khandwala, Manu Chopra.[pdf]Abraham Starosta-Typeguess.Baris Akis, Mariano Sorgente.[pdf]Predicting Usefulness of Yelp Reviews.Ben Isaacs, Xavier Mignot, Maxwell Siegelman.[pdf]Predicting Soccer Results in the English Premier League.Ben Ulmer, Matt Fernandez.[pdf]Detecting Heart Abnormality using ECG with CART.Ben Zhou, Gaspar Garcia, Paurakh Rajbhandary.[pdf]Down and Dirty with Data.Bharat Arora, Roger Davidson, Christopher Wildman.[pdf]Hierarchical Classification of Amazon Products.Bin Wang, Shaoming Feng.[pdf]Predicting high-risk countries for political instability and conflict.Blair Huffman, Emma Marriott, April Yu.[pdf]Machine Learning Implementation in live-cell tracking.Bo Gu.[pdf]Any Given Sunday.Bobak Moallemi, Matthew Wilson, Steven Hoerning.[pdf]P300 Error Detection.Boyeaux Felix,Chatoor Nehan.[pdf]Automated Canvas Analysis for Painting Conservation.Brendan Tobin.[pdf]Office Appliance Classification.Brock Petersen, Gerrit de Moor, Elissa Goldner.[pdf]Sentiment Analysis on Movie Reviews.Cai Xiao, Ya Wang.[pdf]Predicting Mobile Application Success.Cameron Tuckerman.[pdf]Modeling Activity Recognition Using Physiological Data Collected from Wearable Technology.Cezanne Camacho, Jennifer Li, Jeffrey Yang.[pdf]Neural Network Joint Language Model.Charles Qi.[pdf]Yelp Recommendation System Using Advanced Collaborative Filtering.Chee Hoon Ha.[pdf]Prediction of Yelp Review Star Rating using Sentiment Analysis.Chen Li, Jin Zhang.[pdf]Classification of Bad Accounts in Credit Card Industry.Chengwei Yuan.[pdf]Classification Of Musical Playing Styles.Chet Gnegy.[pdf]Email Filtering By Response Required.Chris Knight.[pdf]Forecasting Utilization in City Bike-Share Program.Christina Lee, David Wang, Adeline Wong.[pdf]Recommender.Christopher Aberger.[pdf]Predicting Cell Type-Specific Chromatin States from Genetic Regulatory Networks.Christopher Probert, Anthony Ho.[pdf]Pose Estimation Based on 3D Models.Chuiwen Ma, Liang Shi.[pdf]Visual Localization and POMDP for Autonomous Indoor Navigation.Chulhee Yun, Sungjoon Choi.[pdf]Contours and Kernels-The Art of Sketching.Dan Guo,Paula Kusumaputri,Amani Peddada.[pdf]Indoor Positioning System Using Wifi Fingerprint.Dan Li, Le Wang, Shiqi Wu.[pdf]Predicting air pollution level in a specific city.Dan Wei.[pdf]Prediction of Transcription Factors that Regulate Common Binding Motifs.Dana Wyman, Emily Alsentzer.[pdf]Multi-class motif discovery in keratinocyte differentiation.Daniel Kim.[pdf]Defensive Unit Performance Analysis.Daniel ONeel, Reed Johnson.[pdf]Diagnosing Malignant versus Benign Breast Tumors via Machine Learning Techniques in High Dimensions.Danielle Maddix.[pdf]Hacking the Hivemind.Daria Lamberson,Leo Martel, Simon Zheng.[pdf]Diagnosing Parkinson’s from Gait.Daryl Chang, Marco Alban-Hidalgo, Kevin Hsu.[pdf]Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification.Dashiell Bodington, Eric Greenstein, Matthew Hu.[pdf]Vignette.David Eng, Andrew Lim, Pavitra Rengarajan.[pdf]Machine Learning In JavaScript.David Frankl.[pdf]Searching for exoplanets in the Kepler public data.David Glass, Xiaofan Jin.[pdf]Model Clustering via Group Lasso.David Hallac.[pdf]Improving Positron Emission Tomography Imaging with Machine Learning.David Hsu.[pdf]Algorithmic Trading of Futures via Machine Learning.David Montague.[pdf]Topic based comments exploration for online articles.Deepak Zambre, Ajey Shah.[pdf]Personal Legal Counselor and Interpreter of the Law via Machine Learning.Derek Yan, Tianyi Wang, Patrick Chase.[pdf]Personalized Web Search.Dhanraj Mavilodan, Kapil Jaisinghani, Radhika Bansal.[pdf]Detecting Ads in a Machine Learning Approach.Di Zhang.[pdf]Predicting Mitochondrial tRNA Modification.Diego Calderon.[pdf]Collaborative Neighborhoods.Diego Represas, David Dindi.[pdf]Estimation of Causal Effects from Observational Study of Job Training Program.Dmitry Arkhangelsky, Rob Donnelly.[pdf]Deep Leraning Architecture for Univariate Time Series Forecasting.Dmitry Vengertsev.[pdf]Solomon.Do Kwon, Gyujin Oh, Ki Suk Jang, Ji Park.[pdf]Automatic detection of nanoparticles in tissue sections.Dor Shaviv, Orly Liba.[pdf]Implementation of Deep Convolutional NeuralNet on a DSP.Elaina Chai.[pdf]Evergreen or Ephemeral – Predicting Webpage Longevity Through Relevancy Features.Elaine Zhou, Lingtong Sun.[pdf]MacMalware.Elizabeth Walkup.[pdf]Extractive Fiction Summarization Using Sentence Significance Scoring Models.Eric Holmdahl, Ashkon Farhangi, Lucio Tan.[pdf]Identifying And Predicting Market Reactions To Information Shocks In Commodity Markets.Eric Liu, Vedant Ahluwalia, Deepyaman Datta, Dongyang Zhang.[pdf]An EM-Derived Approach to Blind HRTF Estimation.Eric Schwenker.[pdf]The Many Dimensions of Net Neutrality.Erin Antono, Deger Turan, Justine Zhang.[pdf]Learning To Predict Dental Caries For Preschool Children.Fangzhou Guo, Huaiyang Zhong, Yuchen Li.[pdf]Information based feature selection.Farzan Farnia, Abbas Kazerouni, Afshin Babveyh.[pdf]Identifying Elephant Vocalizations.Flavia Crisrtina Grey Rodriguez, Sergio Patricio Figueroa Sanz.[pdf]Predicting Protein Fragment Binding.Flynn Wu.[pdf]Bike Share Usage Prediction in London.Ford Rylander, Bo Peng, Jeff Wheeler.[pdf]Localized Explicit Semantic Analysis.Francis Lewis.[pdf]Robo Brain Massive Knowledge Base for Robots.Gabriel Kho, Christina Hung, Hugh Cunningham.[pdf]Understanding Music Genre Similarity.Gabriela Groth.[pdf]Correlated Feature Selection for Single-Cell Phenotyping.Geoff Stanley.[pdf]Activity Recognition in Construction Sites Using 3D Accelerometer and Gyrometer.Gustavo Cezar .[pdf]Event-based stock market prediction.Hadi Pouransari, Hamid Chalabi.[pdf]Recommendation Based On User Experience.Hai Vu.[pdf]Spectrum Adaptation in Multicarrier Interference Channels.Haleema Mehmood.[pdf]Exploring Potential for Machine Learning on Data About K-12 Teacher Professional Development.Hamilton Plattner.[pdf]Player Behavior and Optimal Team Compositions for Online Multiplayer Games.Hao Yi Ong, Sunil Deolalikar, Mark Peng.[pdf]Algorithmic Trading Strategy Based On Massive Data Mining.Haoming Li, Tianlun Li, Zhijun Yang.[pdf]Face Detection And Recognition Of Drawn Characters.Herman Chau.[pdf]Gene Expression Analysis Of HCMV Latent Infection.Hie Hong.[pdf]A New Kalman Filter Method.Hojat Ghorbanidehno, Hee Sun Lee.[pdf]Using Tweets for single stock price prediction.Hongshan Chu, Ye Tian, Hongyuan Yuan.[pdf]Classification of Human Posture and Movement Using Accelerometer Data.Huafei Wang, Jennifer Wu.[pdf]Naïve Bayes Classifier And Profitability of Options Gamma Trading.HyungSup Lim.[pdf]Vector-based Sentiment Analysis of Movie Reviews.Ian Roberts, Lisa Yan.[pdf]A General-Purpose Sentence-Level Nonsense Detector.Ian Tenney.[pdf]Characterizing Genetic Variation in Three Southeast Asian Populations.Ilana Arbisser, Jonathan Kang.[pdf]Machine Learning for the Smart Grid.Iliana Voynichka.[pdf]Predicting Africa Soil Properties.Iretiayo Akinola, Thomas Dowd.[pdf]Automated Bitcoin Trading via Machine Learning Algorithms.Isaac Madan, Shaurya Saluja, Aojia Zhao.[pdf]SkatBot.Ivan Leung, Pedro Milani, Ben-han Sung.[pdf]Tradeshift Text Classification.Jacob Conrad Trinidad, Ian Torres.[pdf]New York City Bike Share.James Kunz, Everett Yip, Gary Miguel.[pdf]Predicting Seizure Onset in Epileptic Patients Using Intercranial EEG Recordings.Janet An, Amy Bearman, Catherine Dong.[pdf]Predicting Foster Care Exit.Jason Huang.[pdf]Yelp Recommendation System.Jason Ting, Swaroop Indra Ramaswamy.[pdf]Predicting National Basketball Association Game Winners.Jasper Lin, Logan Short, Vishnu Sundaresan.[pdf]Predicting Yelp Ratings From Business and User Characteristics.Jeff Han, Justin Kuang, Derek Lim.[pdf]Predicting Popularity of Pornography Videos.Jessie Duan.[pdf]Accurate Campaign Targeting Using Classification Algorithms.Jieming Wei, Sharon Zhang.[pdf]Forecasting Bike Rental Demand.Jimmy Du, Rolland He, Zhivko Zhechev.[pdf]Predicting User Following Behavior On Tencent Weibo.Jinfeng Huang, Hai Huang, Zhaoyang Jin .[pdf]Improving Taxi Revenue With Reinforcement Learning.Jingshu Wang, Benjamin Lampert.[pdf]Learning Facial Expressions From an Image.Jithin Thomas, Bhrugurajsinh Chudasama, Chinmay Duvedi.[pdf]All Your Base Are Belong To Us English Texts Written by Non-Native Speakers.Joanna Kim, Jonathan Hung.[pdf]Identifying Regions High Turbidity.Joe Adelson.[pdf]A Comparison of Classification Methods for Expression Quantitative Trait Loci.Joe Davis.[pdf]Predicting Mobile Users Future Location.John Doherty .[pdf]Machine Learning Madness.John Gold, Elliot Chanen.[pdf]Semi-Supervised Learning For Sentiment Analysis.John Miller, Aran Nayebi, Amr Mohamed.[pdf]Legal Issue Spotting.John Phillips.[pdf]A novel way to Soccer Match Prediction.Jongho Shin, Robert Gasparyan.[pdf]Morphological Galaxy Classification.Jordan Duprey, James Kolano.[pdf]Predicting Helpfulness Ratings of Amazon Product Reviews.Jordan Rodak, Minna Xiao, Steven Longoria.[pdf]Predicting Course Completions For Online Courses.Joseph Paetz.[pdf]An Adaptive System For Standardized Test Preparation.Julia Enthoven.[pdf]Single Molecule Biophysics Machine Learning For Automated Data Processing.Junhong Choi, Soomin Cho.[pdf]Understanding Comments Submitted to FCC on Net Neutrality.Junhui Mao, Jing Xia, Woncheol Jeong.[pdf]Direct Data-Driven Methods for Decision Making under Uncertainty.Junjie Qin.[pdf]From Food To Wine.Justin Meier.[pdf]Classifying Legal Questions into Topic Areas Using Machine Learning.Karthik Jagadeesh, Brian Lao.[pdf]Predicting Hit Songs with MIDI Musical Features.Kedao Wang.[pdf]Machine Learning Methods for Biological Data Curation.Kelley Paskov.[pdf]Classifying Forest Cover Type using Cartographic Features.Kevin Crain, Graham Davis.[pdf]Peer Lending Risk Predictor.Kevin Tsai,Sivagami Ramiah,Sudhanshu Singh.[pdf]Learning Distributed Representations of Phrases.Konstantin Lopyrev.[pdf]Estimation Of Word Representations Using Recurrent Neural Networks And Its Application In Generating Business Fingerprints.Kuan Fang.[pdf]Gender Identification by Voice.Kunyu Chen.[pdf]Applications Of Machine Learning To Predict Yelp Ratings.Kyle Carbon, Kacyn Fujii, Prasanth Veerina.[pdf]Methodology for Sparse Classification Learning Arrhythmia.Lee Tanenbaum.[pdf]Predicting March Madness.Levi Franklin.[pdf]Net Neutrality Language Analysis.Li Tao, Xinyi Xie.[pdf]Characterizing Atrial Fibrillation Burden for Stroke Prevention.Lichy Han.[pdf]Predict Seizures in Intracranial EEG Recordings.Linyu He, Lingbin Li.[pdf]Automated Music Track Generation.Louis Eugene, Guillaume Rostaing.[pdf]Characterizing Overlapping Galaxies.Luis Alvarez.[pdf]Understanding Player Positions in the NBA.Luke Lefebure.[pdf]Cross-Domain Product Classification with Deep Learning.Luke de Oliveira, Alfredo Lainez, Akua Abu.[pdf]Predicting Heart Attacks.Luyang Chen, Qi Cao, Sihua Li, Xiao Ju.[pdf]Prediction of Bike Sharing Demand for Casual and Registered Users.Mahmood Alhusseini.[pdf]Classification Of Arrhythmia Using ECG Data.Manas Karandikar, Giulia Guidi.[pdf]What Can You Learn From Accelerometer Data.Manikantan Shila.[pdf]Speaker Recognition for Multi-Source Single-Channel Recordings.Maria Frank, Neil Gallagher, Jose Kruse Perin.[pdf]Prediction of consumer credit risk.Marie-Laure Charpignon, Enguerrand Horel, Flora Tixier.[pdf]Machine Learning for Network Intrusion Detection.Martina Troesch, Ian Walsh.[pdf]Predicting Paper Counts in the Biological Sciences.Matt Denton, Jose Hernandez, Debnil Sur.[pdf]Prediction of Price Increase for MTG Cards.Matt Pawlicki, Joe Polin, Jesse Zhang.[pdf]Twitter Classification into the Amazon Browse Node Hierarchy.Matthew Long, Jiao Yu, Anshul Kundani.[pdf]Determining Mood From Facial Expressions.Matthew Wang, Spencer Yee.[pdf]Visualizing Personalized Cancer Risk Prediction.Maulik Kamdar.[pdf]Predicting the Total Number of Points Scored in NFL Games.Max Flores, Ajay Sohmshetty.[pdf]Short Term Power Forecasting Of Solar PV Systems Using Machine Learning Techniques.Mayukh Samanta,Bharath Srikanth,Jayesh Yerrapragada.[pdf]Star-Galaxy Separation in the Era of Precision Cosmology.Michael Baumer, Noah Kurinsky, Max Zimet.[pdf]Artist Attribution via Song Lyrics.Michael Mara.[pdf]Accelerometer Gesture Recognition.Michael Xie, David Pan.[pdf]Arrythmia Classification for Heart Attack Prediction.Michelle Jin.[pdf]#ML#NLP-Autonomous Tagging Of Stack Overflow Posts.Mihail Eric, Ana Klimovic, Victor Zhong.[pdf]Scheduling Tasks Under Constraints.Mike Yu,Dennis Xu,Kevin Moody.[pdf]Classification Of Beatles Authorship.Miles Bennett, Casey Haaland, Atsu Kobashi.[pdf]Classification of Accents of English Speakers by Native Language.Morgan Bryant, Amanda Chow, Sydney Li.[pdf]Exposing commercial value in social networks matching online communities and businesses.Murali Narasimhan, Camelia Simoiu, Anthony Ward.[pdf]Hacking the genome.Namrata Anand.[pdf]How Hot Will It Get Modeling Scientific Discourse About Literature.Natalie Telis.[pdf]Permeability Prediction of 3-D Binary Segmented Images Using Neural Networks.Nattavadee Srisutthiyakorn.[pdf]Automated Identification of Artist Given Unknown Paintings and Quantification of Artistic Style.Nicholas Dufour, Kyle Griswold, Michael Lublin.[pdf]Predicting Lecture Video Complexity.Nick Su, Ismael Menjivar.[pdf]Result Prediction of Wikipedia Administrator Elections based ondNetwork Features.Nikhil Desai, Raymond Liu, Catherine Mullings.[pdf]Predicting The Treatment Status.Nikolay Doudchenko.[pdf]Error Detection based on neural signals.Nir Even-Chen, Igor Berman.[pdf]Speech Similarity.OReilly Mavrommatis.[pdf]Data-Driven Modeling and Control of an Autonomous Race Car.Ohiremen Dibua, Aman Sinha, and John Subosits.[pdf]Predicting the Diagnosis of Type 2 Diabetes Using Electronic Medical Records.Oliver Bear Dont Walk IV, David Joosten, Tim Moon.[pdf]A Novel Approach to Predicting the Results of NBA Matches.Omid Aryan, Ali Reza Sharafat.[pdf]Automatically Generating Musical Playlists.Paul Martinez.[pdf]Solar Flare Prediction.Paul Warren,Gabriel Bianconi.[pdf]Application of machine learning techniques for well pad identification inathe Bakken oil fielda.Philip Brodrick, Jacob Englander.[pdf]Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods.Phillip Pham,Steven Li.[pdf]Two-step Semi-supervised Approach for Music Structural Classificiation.Prateek Verma, Yang-Kai Lin, Li-Fan Yu.[pdf]Domain specific sentiment analysis using cross-domain data.Praveen Rokkam, Marcello Hasegawa.[pdf]Instrumental Solo Generator.Prithvi Ramakrishnan, Aditya Dev Gupta.[pdf]Cross-Domain Text Understanding in Online SocialData.Qian Lin, Shenxiu Liu, Zhao Yang.[pdf]From Paragraphs to Vectors and Back Again.Qingping He.[pdf]HandwritingRecognition.Quan Nguyen, Maximillian Wang, Le Cheng Fan.[pdf]Chemical Identification with Chemical Sensor Arrays.Quintin Stedman.[pdf]Genre Classification Using Graph Representations of Music.Rachel Mellon, Dan Spaeth, Eric Theis.[pdf]Collaborative Filtering Recommender Systems.Rahul Makhijani, Saleh Samaneh, Megh Mehta.[pdf]Detecting The Direction Of Sound With A Compact Microphone Array.Rajewski.[pdf]Finding Undervalued Stocks With Machine Learning.Ramneet Rekhi, Huan Wei, Tucker Ward, Michael Downs.[pdf]Multilevel Local Search Algorithms for Modularity Clustering.Randolf Rotta, Andreas Noack.[pdf]Automated Detection and Classification of Cardiac Arrhythmias.Richard Tang, Saurabh Vyas.[pdf]Predicting Kidney Cancer Survival From Genomic Data.Rishi Bedi, Duc Nguyen, Christopher Sauer, Benedikt Buenz.[pdf]Multiclass Sentiment Analysis of Movie Reviews.Robert Chan, Michael Wang.[pdf]Classification and Regression Approaches to Predicting US Senate Elections.Rohan Sampath, Yue Teng.[pdf]Learning from Quantified Self Data.Roshan Vidyashankar.[pdf]Predict Influencers in the Social Network.Ruishan Liu, Yang Zhao, Liuyu Zhou.[pdf]Bias Detector.Rush Moody.[pdf]Constructing Personal Networks Through Communication History.Ryan Houlihan, Hayk Matirosyan.[pdf]Modeling Protein Interactions Using Bayesian Networks.Sabeek Pradhan, Shayne Longpre, Varun Vijay.[pdf]Topic Analysis of the FCC’s Public Comments on Net Neutrality.Sachin Padmanabhan, Leon Yao, Luda Zhao, Timothy Lee.[pdf]Predicting Hospital Readmissions.Sajid Zaidi.[pdf]Analyzing Positional Play in Chess Using Machine Learning.Sameep Bagadia, Pranav Jindal, Rohit Mundra.[pdf]Yelp Restaurants’ Open Hours.Samuel Bakouch, Adrien Boch, Benjamin Favreau.[pdf]Identifying Arrhythmia from Electrocardiogram Data.Samuel McCandlish, Taylor Barrella.[pdf]Diagnosing and Segmenting Brain Tumors and Phenotypes using MRI Scans.Samuel Teicher, Alexander Martinez.[pdf]Exploring the Genetic Basis of Congenital Heart Defects.Sanjay Siddhanti, Jordan Hannel, Vineeth Gangaram.[pdf]Attribution of Contested and Anonymous Ancient Greek Works.Sarah Beller, James Spicer.[pdf]Object Detection for Semantic SLAM using Convolutional Neural Networks.Saumitro Dasgupta.[pdf]Sentiment as a Predictor of Wikipedia Editor Activity.Sergio Martinez-Ortuno, Deepak Menghani, Lars Roemheld.[pdf]Blowing Up The Twittersphere- Predicting the Optimal Time to Tweet.Seth Hildick-Smith, Zach Ellison.[pdf]Evergreen Classification_ Exploring New Features.Shailesh Bavadekar.[pdf]Detecting Lane Departures Using Weak Visual Features.Shane Soh, Ella Kim.[pdf]Re-clustering of Constellations through Machine Learning.Shanshan Xu, Kaifeng Chen, Yao Zhou.[pdf]Application of Neural Network In Handwriting Recognition.Shaohan Xu, Qi Wu, Siyuan Zhang.[pdf]Recognition and Classification of Fast Food Images.Shaoyu Lu, Sina Lin, Beibei Wang.[pdf]Reduced Order Greenhouse Gas Flaring Estimation.Sharad Bharadwaj, Sumit Mitra.[pdf]Blood Pressure Detection from PPG.Sharath Ananth.[pdf]Predicting Low Voltage Events on Rural Micro-Grids in Tanzania.Shea Hughes, Samuel Steyer, Natasha Whitney.[pdf]Amazon Employee Access Control System_Updated_Version.Shijian Tang, Jiang Han, Yue Zhang.[pdf]Prediction Onset Epileptic.Shima Alizadeh, Scott Davidson, Ari Frankel.[pdf]Evaluating Pinch Quality of Underactuated Robotic Hands.Shiquan Wang, Hao Jiang.[pdf]Reinforcement Learning With Deeping Learning in Pacman.Shuhui Qu, Tian Tan,Zhihao Zheng.[pdf]Language identification and accent variation detection in spoken language recordings.Shyamal Buch, Jon Gauthier, Arthur Tsang.[pdf]Enhancing Cortana User Experience Using Machine Learning.Siamak Shakeri, Emad Elwany.[pdf]Who Matters.Sid Basu, David Daniels, Anthony Vashevko.[pdf]Predicting Heart Attacks.Sihang Yu, Yue Zhao, Xuyang Zheng.[pdf]Predicting Seizures in Intracranial EEG Recordings.Sining Ma, Jiawei Zhu.[pdf]Structural Health Monitoring in Extreme Events from Machine Learning Perspective.Sophia Zhou,Jingxuan Zhang.[pdf]On-line Kernel Learning for Active Sensor Networks.Stefan Jorgensen.[pdf]ECommerce Sales Prediction Using Listing Keywords.Stephanie Chen.[pdf]Review Scheduling for Maximum Long-Term Retention of Knowledge.Stephen Barnes, Cooper Frye, Khalil Griffin.[pdf]Adaptive Spaced Repetition.Stephen Koo, Sheila Ramaswamy.[pdf]Do a Barrel Roll.Steven Ingram, Tatiana Kuzovleva.[pdf]Oil Field Production using Machine Learning.Sumeet Trehan.[pdf]Predicting Success for Musical Artists through Network and Quantitative Data.Suzanne Stathatos, Zachary Yellin-Flaherty.[pdf]Better Models for Prediction of Bond Prices.Swetava Ganguli, Jared Dunnmon.[pdf]Classifying the Brain 27s Motor Activity via Deep Learning.Tania Morimoto,Sean Sketch.[pdf]Prediction of Bike Rentals.Tanner Gilligan, Jean Kono.[pdf]Classification of Alzheimer’s Disease Based on White Matter Attributes.Tanya Glozman, Rosemary Le.[pdf]MoralMachines- Developing a Crowdsourced Moral Framework for Autonomous Vehicle Decisions.Tara Balakrishnan, Jenny Chen, Tulsee Doshi.[pdf]Context Specific Sequence Preference Of DNA Binding Proteins.Tara Friedrich.[pdf]Predicting Reddit Post Popularity ViaInitial Commentary.Terentiev Tempest.[pdf]Machine Learning for Continuous Human Action Recognition.Tian Tang.[pdf]Predicting Pace Based on Previous Training Runs.Tiffany Jin.[pdf]Probabilistic Driving Models and Lane Change Prediction.Tim Wheeler.[pdf]Multiple Sensor Indoor Mapping Using a Mobile Robot.Timothy Lee.[pdf]Bone Segmentation MRI Scans.Todor Markov William McCloskey.[pdf]#Rechorder Anticipating Music Motifs In Real Time.Tommy Li, Yash Savani, Wilbur Yang.[pdf]Prediction and Classification of Cardiac Arrhythmia.Vasu Gupta, Sharan Srinivasan, Sneha Kudli.[pdf]Predicting DJIA Movements from the Fluctuation of a Subset of Stocks.Veronique Moore.[pdf]Sentiment Analysis for Hotel Reviews.Vikram Elango, Govindrajan Narayanan.[pdf]Mood Detection with Tweets.Wen Zhang, Geng Zhao, Chenye Zhu.[pdf]Comparison of Machine Learning Techniques for Magnetic Resonance Image Analysis.Wendy Ni, Xinwei Shi, Umit Yoruk.[pdf]Object Recognition in Images.Wenqing Yang, Harvey Han.[pdf]3D Scene Retrieval from Text.Will Monroe.[pdf]Predicting Breast Cancer Survival Using Treatment and Patient Factors.William Chen, Henry Wang.[pdf]Parking Occupancy Prediction and Pattern Analysis.Xiao Chen.[pdf]Supervised DeepLearning For MultiClass Image Classification.Xiaodong Zhou.[pdf]User Behaviors Across Domains .Xiaofei Fu, Norman Yu, Abhishek Garg.[pdf]Seizure forecasting.Xiaoying Pang.[pdf]Stock Trend Prediction with Technical Indicators using SVM.Xinjie Di.[pdf]Predicting Usefulness of Yelp Reviews.Xinyue Liu, Michel Schoemaker, Nan Zhang.[pdf]Obstacles Avoidance with Machine Learning Control Methods in Flappy Birds Setting.Yi Shu, Ludong Sun, Miao Yan, Zhijie Zhu.[pdf]Yelp User Rating Prediction.Yifei Feng, Zhengli Sun.[pdf]Demand Prediction of Bicycle Sharing Systems.Yu-chun Yin, Chi-Shuen Lee, Yu-Po Wong.[pdf]Facial Keypoints Detection.Yue Wang,Yang Song.[pdf]Is Beauty Really In The Eye Of The Beholder.Yun (Albee) Ling, Jocelyn Neff, and Jessica Torres.[pdf]Sentiment Analysis of Yelp’s Ratings Based on Text Reviews.Yun Xu, Xinhui Wu, Qinxia Wang.[pdf]Multiclass Classifier Building with Amazon Data to Classify Customer Reviews into Product Categories.Yunzhen Hu, Te Hu, Haier Liu.[pdf]An Energy Efficient Seizure Prediction Algorithm.Zhongnan Fang, Yuan Yuan, Andrew Weitz.[pdf]Classifier Comparisons On Credit Approval Prediction.Zhoutong Fu, Zhedi Liu.[pdf]Appliance Based Model for Energy Consumption Segmentation.Zi Yin, Thanchanok Teeraratkul, Nutthavuth Tamang.[pdf]analysis on 1s1r array.Zizhen Jiang.[pdf]Video Series:Further 35 Project Ideas or Suggestions which might interest you.1. AI (Artifical Intelligence) Based Image Capturing and transferring to PC/CCTV using Robot2. Material Dimensions Analyzing Robot3. An intelligent mobile robot navigation technique using RFID Technology4. IVRS Based Robot Control with Response & Feed Back5. Library Robot – Path Guiding Robotic System with Artificial Intelligence using Microcontroller6. Wireless Artificial Intelligence Based Fire Fighting Robot for Relief Operations7. A Humanoid Robot to Prevent Children Accidents8. Motion Detection, Robotics Guidance & Proximity Sensing using Ultrasonic Technology9. Robust Sensor-Based Navigation for Mobile Robots10. Visual tracking control to fast moving target for stereo vision robot11. A Voice Guiding System for Autonomous Robots12. Artificial Intelligent based Solar Vehicle13. Mobile robot control based on information of the scanning laser range sensor14. Walking Robot with Infrared Sensors / Light Sensors / RF Sensor / Tactile Sensors15. IVRS Based Control of Three Axis Robot With Voice Feed back16. Intelligent Mobile Robot for Multi Specialty Operations17. Sensor Operated Path Finding Robot (Way Searching)18. Design and Development of Obstacle Sensing and Object Guiding Robot19. SMS controlled intelligent searching and pick and place moving robot20. Artificial Intelligence Based Image Capturing and Transferring to PC using Robot21. Artificial Intelligent Based Remote controlled Automatic Path finding Cum Video Analyzing Robot22. Wall Follower Robot with The Help of Multiple Artificial Eyes23. Sensor Operated Automatic Punching robot24. Fire Fighting Robotics with AI (Artificial Intelligence) and WAP25. Intelligent Robot with Artificial Intelligence computer Brain system26. Remote controlled Pneumatic Four Axis Material Handling Robot27. Advanced Robotic Pick and Place Arm and Hand System28. Voice Controlled Material handling Robot29. A Hands Gesture Control System of for an Intelligent Robot30. Robotic Vision and Color Identification System with Solenoid Arm for Colored Material Separation31. Artificial Intelligence Based Fire fighting AGV32. SMS controlled video analyzing robot33. Staircase Climbing Robot – Implemented in Multi-Domain Approach34. Fully Automated Track Guided Vehicle (ATGV) Robot35. PC based wireless Pick and Place jumping robot with remote control36. Three Axis Robotics With Artificial Intelligence (AI)

PDF, or portable document format, was first developed as a file format in the 1993 by signNow, with the now ubiquitous red signNow A/triangle infinity swoop icon. Since 2008, PDF has been an ISO standard (ID 32000-2), and an open format, which means that anyone can use it without paying royalties to signNow. The original colors stuck around though, as most readers use the red colors which were initially part of signNow’s logo. Since becoming an open format though, the PDF market has changed dramatically, with the introduction of highly efficient apps, which work on mobile devices, like Kdan Mobile’s PDF Reader. If you’re looking for a great PDF reader that has all of the best editing functions, which you can download for free, as part of the Kdan team, I highly recommend that you try this PDF Reader. It’s trusted by over 50 million downloads, and is packed with cool features, to help users accomplish all of their everyday document editing tasks with ease. It was even promoted to the App of the Year on the Google Play Store, and best Productivity on the iTunes App Store, so you’ve probably seen it before. What makes it different, is that although it is free to download, you still have many editing functions only seen in premium paid apps, like combine PDF, edit pages, and even signatures. With signatures, you can edit, add form data, and sign with a legally valid signature, or request signatures from others with a built-in cloud based document management system, all from one app. If you want to see one of the most feature-rich PDF readers on the market today, with support for iOS, Android, Windows, and Mac, I highly recommend that you try PDF Reader today.

GST refers to the Goods and Services tax that is levied on the supply of goods and services in India. GST has subsumed several many indirect tax in India hence making the taxation system of India less complex. These indirect taxes that has been subsumed by GST law of India are as follows:Central Excise DutyService TaxCountervailing DutySpecial Countervailing DutyValue Added Tax (VAT)Central Sales Tax (CST)OctroiEntertainment TaxEntry TaxPurchase TaxLuxury TaxAdvertisement taxesTaxes applicable on lotteriesAfter the implementation of GST in India, new laws came into existence, along with which GST registration has evolved that is mandatory for certain businesses of India. This GST registration is required primarily for those businesses who have their annual sales turnover more than 20 Lakhs. Even if the businesses whose sales turnover is below 20 Lakhs, they are also suggested to get registered under GST and this is recommended due to two big reasons. First, these businesses cannot sell outside your state and second reason they will not get the tax refund on purchases. The one and only solution to this is GST registration online in India.The process of GST registration takes approximately 5 – 6 days. For GST registration online, the person need to file the application with the department along with his or her digital signature.Here is a step-by-step guide to get registered under GST online in India:Part AStep 1:Open GST portal on your browserClick on the “Register Now” option given below the “Taxpayers (Normal)”Select “New Registration”You will see two sections for registration:1. User credentials2. OTP verificationStep 2:Fill all the credentials asked for in section 1.Select taxpayerName your stateName your districtName of the businessPAN numberEmail addressMobile number (Separate OTP’s will be sent to the mail Id and the mobile number given)Click on “Proceed”Step 3:You are redirected to the next section that is for OTP verification.Enter the OTP’s that are sent to your registered email id and the mobile number separately.Click on “Continue”Step 4:You will receive the Temporary Reference Number (TRN). This credential will be sent to your mobile number and the email id as well.Click on “Proceed”Step 5:Open GST portal on your browserClick on the “Register Now” option given below the “Taxpayers (Normal)”Complete the credentials given in section 1 for checking the status of the application.Select “Temporary Reference Number (TRN)”Enter the TRNComplete the captcha codeClick on “Proceed”Step 6:You will receive a unique OTP on the registered mobile and email address.Enter the OTP in the “Mobile/Email OTP” sectionClick on “Proceed”Step 7:Status of the application will be shown now. It will be shown as “Draft”Click on Edit Icon.You will be redirected to the next part of the registration process now.Part BStep 1:You need to fill all the details and submit all the required documents in this section.Documents that are asked for submission are:PhotographsConstitution of the taxpayerProof for the place of businessBank account detailsAuthorization formStep 2:Now after filling all the details and once all the documents are submitted, you need to go to the “Verification Page”Enter the asked details and tick the declarationSubmit the application:Either by “Submit with DSC”Or “Submit with e-Sign”Step 3:“Success” message will pop up telling for successful application and an Application Reference Number (ARN) is sent to registered email and mobile.Step 4:For checking the status of ARN, you need to enter the ARN on GST portal.

ProofHubProofHub is a cross-platform utility to take notes in a variety of formats, including text, photos, audio, video, sketches and more. It is one tool you need to keep yourself organized in today’s hectic life. It syncs across all your devices to facilitate workflow. It is one of the essential Android apps for every user.Google KeepDo you remind yourself of important tasks and motivational quotes with sticky notes on your desktop monitor? Or maybe you’ve replaced those with Stickies on your Mac, or Windows 10’s Sticky Notes. Google Keep is your next best alternative to keep those notes on all your devices. It’s a sticky note app that works everywhere, with digital copies of the standard sticky note colors.Add its extension to Chrome, then whenever you come across a website you want to remember—or have an idea you don’t want to forget—you can add it to Google Keep. List tasks and shopping lists with bullet points, or add reminders to the most important things so you don’t forget them. If you want to use the notes in your work, the Google Keep sidebar in Google Docs lets you drag notes into your documents to pull research and ideas together into a finished piece.PocketTo save anything online for laterBookmarks are broken. They started as a way to save your favorite websites—and over time, we favorited so many sites, it got tough to find stuff in our bloated bookmarks menus. It’s almost easier to Google things each time than to search for their bookmark.So put your essential sites in the favorites menu, or let your browser decide and show the sites you visit most. Then add the rest to Pocket. It’s a to-do list for websites, a place to save the articles you want to read and videos you want to watch. Tap the Pocket button in your browser to file something away. Then when you have time, you’ll always have something to read or watch without searching for a nearly-hidden bookmark.MindMeisterTo mind map your ideasYou have ideas, but you can’t quite figure out how to put them all together. MindMeister’s mind maps make that easier. Double-click anywhere on its canvas to add a new idea. List everything in your mind. Get your team to help, adding as many solutions to a problem as they can.Then group similar ideas together, link related concepts to each other, and before long you’ll have a detailed map that traces everything back to a central thesis. Mind maps are a great way to sketch your ideas and figure things out on paper, and with MindMeister, you can take your ideas anywhere, collaborate on them with your team, and turn your finished ideas into action plans with its companion MeisterTask project tool.signNowTo digitally sign documentsNeed to sign a document—or dozens of them? Don’t print them out, pull out a pen, then scan the signed documents. Instead, signNow helps you sign every page that needs your signature in a few clicks. Draw your signature on signNow’s mobile apps, or type your name and let signNow generate a signature if you’d prefer, then click each signature field to add it. You can make template documents in signNow, too, so you don’t waste time in Word making new contracts and agreements every time you need someone to sign something.FoxitTo view and edit PDF filesPDF files are the digital equivalent to paper, the most common way to share legal documents, forms, briefs, design drafts, and formatted eBooks. You can open PDFs on most devices, and Chrome includes a PDF viewer for online files. If you need additional features, Foxit’s core apps let you work with PDFs from any device.You can view or edit PDF files in Foxit Online’s editor, convert existing files to PDF format, or sign PDF forms without downloading Acrobat. If you need to fix something in an existing PDF, you can edit it online or in Foxit’s desktop and mobile apps, with a variety of PDF-powered apps for different business needs. They’re a handy way to do more with PDF files from anywhere.ScanbotTo scan and fax documents from your phone or tabletScanbot's not a universal app. It doesn’t work in your browser, or on a desktop or laptop. But those aren’t best for scanning documents anyhow—your phone’s a far better choice. And there, it's a great scanning tool.Open Scanbot, point your camera at a document, and it’ll snap a clean scan even if your phone isn’t perfectly level. You can then save the file to Google Drive for free OCR—or use its in-app purchases to recognize text, annotate the scanned document, and even fax it directly from your phone. It’s a great companion to the other productivity apps that do work great on your computer.

Creating a movie trailer!Last year, 20th Century Fox released a trailer (watch here), claiming to be the first one created by AI/Machine Learning (IBM Watson). The movie was an AI horror thriller, Morgan.In spite of headlines like Watch: IBM's Watson Created a Super Creepy Movie Trailer All By Itself, Watson did not do it all by itself. All Watson did was choosing 10 scenes (totaling 6 minutes of footage) from the movie that should appear in the trailer, and a human film maker then edited the scenes together and added the musical overlay.Nevertheless, it’s impressive. On a high-level, here’s how Watson chose those 10 scenes:Humans first looked at the trailers of 100 horror movies and labeled each scene of each trailer as ‘eerie’, ‘frightening’, ‘tender’, etc.Watson then analyzed the audio and video of those scenes to learn what the scenes and the corresponding labels mean. For example, it could have learnt something like:Soothing music + Child smiling = Tender scene.Silence + Person crying = Sad scene.Creaking sound + Door opening slowly = Suspenseful scene.Scream + Gory face for 1 millisecond = Scary scene.Watson now knows what kind of scenes typically appear in a horror movie trailer, in terms of audio and video features.Watson was then fed the full-length movie (Morgan). It analyzed the audio and video features of all scenes in the movie, and identified 10 scenes that would be the best candidates for a trailer.That's how the 10 scenes were chosen. And according to IBM’s blog, Watson helped reduce what could be a weeks-long process to just one day.But make no mistake, this is not equivalent to machines learning creativity or even just fear. As far as most visual features are concerned, any ML system probably treats Samara coming out of the TV in The Ring and a baby crawling out of a crib as almost the same thing.