Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-data-science
Laundry List of Data Science / ML /AI resources available online
https://github.com/sayantansatpati/awesome-data-science
- Coursera: Andrew NG
- Coursera: Geoffrey Hinton
- Caltech: Abu Mostafa
- Stanford: NLP cs224n
- Stanford: CNN cs231n - CNNs), [Spring 2017](https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv&app=desktop)
- Stanford: MMDS
- Berkeley: Deep Reinforcement Learning
- Stanford: Convex Optimization
- Stanford: Probabilistic Graphical Models
- Big Data University: TensorFlow
- Kadenze: TensorFlow
- Udacity Nanodegree: AI
- Udacity Nanodegree: Self Driving Car
- EDX: Berkeley X-Series Spark
- Oxford Deep NLP: 2017 SLides Only
- Khan Academy: Linear Algebra
- Khan Academy: Calculus
- MIT: Linear Algebra
- MIT: Calculus
- Harvard: Stat110
- Stanford: cs231n Winter 2016 lectures
- Bay Area Deep Learning School
- 1st Day
- 2nd Day
- Deep Learning Summer School, Montreal
- TensorFlow Without a PhD
- arxiv
- gitxiv
- Deep Learning Reading List
- Hacker Dojo Deep Learning Study Papers
- Deep Learning Papers Reading Roadmap
- Awesome Deep Vision
- The-9-Deep-Learning-Papers-You-Need-To-Know-About
- awesome-deep-learning-papers
- Arthur Chan's Top-5 DL
- top-10-data-science-github
- Awesome Data Science
- Awesome Machine Learning
- Awesome Deep Learning
- Awesome Deep Vision
- Awesome Artifical Intelligence
- awesome-deep-learning-papers
- A-gallery-of-interesting-Jupyter-and-IPython-Notebooks
- Collection of Data Science iPython Notebooks
- Stanford: cs231n
- Adrej Karpathy
- Hvass-Labs: TensorFlow Tutorial Notebooks
- machine-learning-for-software-engineers
- data-scientists-to-follow-best-tutorials
- Oxford Deep NLP: 2017
- colah's blog
- iamtrask
- Medium
- KDNuggets
- datasciencecentral
- machinelearningmastery
- Edwin Chen's blog
- Hunch
- frequently-updated-machine-learning-blogs
- Arthur Chan's Blog
- Neural Networks and Deep Learning
- Deep Learning Book
- An Introduction to Statistical Learning
- The Elements of Statistical Learning
- A Course in Machine Learning
- cs229: ML Course Materials
- KDNuggets: data-science-machine-learning-cheat-sheets
- TensorFlow
- Tensorflow for Deep Learning Research
- TensorFlow-Examples
- pytorch-tutorial
- learning-deep-learning-my-top-five-resource
- yes-you-should-understand-backprop
- Neural Network in Python
- Step By Step Backpropagation
- Andrej Karpathy's lecture
- Christopher Olah on how LSTMs work
- RNN using TensorFlow
- Andrej Karpathy's Blog
- Open Source Data Science Masters
- analyticsvidhya: 21 Deep Learning Videos (2016)
- analyticsvidhya: Top YouTube Videos (2015)
- Free Python Books
- 16 Free Machine Learning Books
- frequently-updated-machine-learning-blogs
- What-are-the-best-machine-learning-blogs-or-resources-available
- How-do-I-learn-machine-learning-1
- What-are-some-good-books-papers-for-learning-deep-learning
- Visual Information Theory
- 4 Steps for Learning Deep Learning
- How to build a Recurrent Neural Network in TensorFlow (1/7)
- Understanding-LSTMs
- anyone-can-code-lstm
Programming Languages
Keywords
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