Cheatsheets, Glossary, Forums, Blogs, articles and more in Machine Learning
A Wiki for Call for papers in Computer science, Artificial intelligence, Machine learning, Security, Data mining. WikiCFP is a semantic wiki for Calls For Papers in science and technology fields with about 50,000 CFPs on WikiCFP. Over 100,000 researchers use WikiCFP each month.
A curated list of the most cited deep learning papers (2012-2016)
A curated list of awesome GAN applications and demonstrations on github with links to paper and their github code
Important papers in ImageNet Classification, Object Detection, Object Tracking, Low-Level Vision, Super-Resolution, Other Applications, Edge Detection, Semantic Segmentation, Visual Attention and Saliency, Object Recognition, Human Pose Estimation, Understanding CNN, Image and Language , Image Captioning, Video Captioning, Question Answering, Image Generation,
Also this github page links to many Courses, Books, Videos, Software, Framework, Applications, Tutorials, Blogs in Computer vision
A curated list of resources dedicated to Recurrent Neural Networks with Codes, Theory, Lectures, Books / Thesis, Architecture Variants (Structure, Memory), Surveys, Applications in Natural Language Processing: Language Modeling, Speech Recognition, Machine Translation, Conversation Modeling, Question Answering, Computer Vision: Object Recognition, Image Generation, Video Analysis, Multimodal (CV+NLP), Image Captioning, Video Captioning, Visual Question Answering, Robotics, Datasets, Blogs, Online Demos
Discover open source deep learning code and pretrained models over categories like Computer Vision, NLP, Generative Models, Reinforcement Learning, Unsupervised Learning, Audio and Video using popular libraries like Tensorflow, Pytorch, Caffe, MXNet, Keras, Chainer.
A list (350+) of all named GANs in a github page and the links to their paper/publication
A website with a cheat sheet containing as many of neural network architectures with easy to understand diagrams and explanations and links to the original paper
The Most Complete List of Best AI Cheat Sheets. From graphs, diagrams to mathematical equations, this medium page has it all. You can download PDF cheat sheets of python, numpy, keras, pandas, scipy, tensorflow, data wrangling, matplotlib, pyspark and more at one place.
Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more.
Tinker with a Neural network in your browser. Visualize and understand the working of a neural network
Deep Learning papers reading roadmap for anyone who are eager to learn this area
A must read online textbook for all deep learning practitioners
A very good site with reading list, links to software, datasets, a list of deep learning research groups, a list of announcements for deep learning related jobs (job listings), as well as tutorials and cool demos.
This blog has lots of topics from Machine learning with references to lots of publications. This blog is very informative and brings the latest news from Google AI.
Although google claims to bring the latest news from Research at Google, most of the posts are from 2018
Although google claims to bring the latest news from Research at Google, most of the posts are from 2018
Very informative blog from Andrej Karpathy. Suggested to visit his stanford website.
Complete, stand alone interpretation of Stanford's machine learning course presented by Andrew Ng
The author of Machine Learning with Python Cookbook shares technical notes on topics in Machine learning, Deep learning, Python, Statistics, Scala, Regular expressions, PostgreSQL, AWS and more.
With more than 475 datasets in Classification, Regression, Clustering with Categorical, Numerical, Mixed attribute types.
Collection of novel and benchmark datasets curated by UCD Researchers, used in their experimental work
Easy to use ML library with lots of code samples, figures and explanations. Start to code ML from here
From databricks
Stanford course with slides, lecture notes and code offered in Stanford University
Reddit page for Machine Learning
When you jump into Deep Learning, you would want to come back to this amazing blog series accompanied by youtube tutorials
Primer for non-technical people who want to understand what machine learning makes possible.
A complete daily plan for studying to become a machine learning engineer. Author approaches the learning part by hands-on and abstracts most of the Math for the beginner
Data Science Stack Exchange is a QnA site for Data science professionals, Machine Learning specialists, and those interested in learning more about the field
This website offers resources, code tutorials, guides, concepts explainers and more for data scientists
Free online book that can help students from non-computer science background to understand concepts of Neural networks and Deep learning
Index page for all terms from A to Z in Mathematics with examples and figures
Course offered by Department of CS, University of Helsinki
Expository text, interactive web apps, data sets, biographical sketches, and an object library
Automated information extraction and co-reference for topics, people and queries
Encog is a pure-Java/C# machine learning framework created back in 2008 to support NEAT, HyperNEAT, Genetic Programming and other neural network technologies
Lots of articles and help on Big data, Machine Learning, Python, Go, Qt and more
Practical Tools and Tutorials for Text Mining and NLP like Sentence Clustering API, Text Similarity API and ROUGE
Google's fast-paced, practical introduction to machine learning. A self-study guide for aspiring machine learning practitioners.