Data Science Resources

A curated list of Data Science resources available online

Table of Contents

• Video Lectures
  • ML and DL MOOCs
  • Mathematics
  • Other Online Video Lectures
• Reading Materials
  • Research Papers
  • GitHub
  • Blogs
  • Online Books
  • Notes
  • Cheat Sheets
  • Misc Others
• Articles
  • Forward and Backpropagation
  • RNN
  • Collection of Useful Resources
  • Quora
  • Misc

Video Lectures

ML and DL MOOCs

1. Coursera: Andrew NG
2. Coursera: Geoffrey Hinton
3. Caltech: Abu Mostafa
4. Stanford: NLP cs224n, Coursera Videos
5. Stanford: CNN cs231n, Videos, Spring 2017
6. Stanford: MMDS
7. Berkeley: Deep Reinforcement Learning
8. Stanford: Convex Optimization
9. Stanford: Probabilistic Graphical Models
10. Big Data University: TensorFlow
11. Kadenze: TensorFlow
12. Udacity Nanodegree: AI
13. Udacity Nanodegree: Self Driving Car
14. EDX: Berkeley X-Series Spark
15. Oxford Deep NLP: 2017 SLides Only

Mathematics

1. Khan Academy: Linear Algebra
2. Khan Academy: Calculus
3. MIT: Linear Algebra
4. MIT: Calculus
5. Harvard: Stat110

Other Online Video Lectures

1. Stanford: cs231n Winter 2016 lectures
2. Bay Area Deep Learning School

• 1st Day
• 2nd Day

3. Deep Learning Summer School, Montreal
4. TensorFlow Without a PhD

Reading Materials

Research Papers

1. arxiv
2. gitxiv
3. Deep Learning Reading List
4. Hacker Dojo Deep Learning Study Papers
5. Deep Learning Papers Reading Roadmap
6. Awesome Deep Vision
7. The-9-Deep-Learning-Papers-You-Need-To-Know-About
8. awesome-deep-learning-papers

Collection of Resources

1. Arthur Chan's Top-5 DL

GitHub

1. top-10-data-science-github
2. Awesome Data Science
3. Awesome Machine Learning
4. Awesome Deep Learning
5. Awesome Deep Vision
6. Awesome Artifical Intelligence
7. awesome-deep-learning-papers
8. A-gallery-of-interesting-Jupyter-and-IPython-Notebooks
9. Collection of Data Science iPython Notebooks
10. Stanford: cs231n
11. Adrej Karpathy
12. Hvass-Labs: TensorFlow Tutorial Notebooks
13. machine-learning-for-software-engineers
14. data-scientists-to-follow-best-tutorials
15. Oxford Deep NLP: 2017

Blogs

1. colah's blog
2. iamtrask
3. Medium
4. KDNuggets
5. datasciencecentral
6. machinelearningmastery
7. Edwin Chen's blog
8. Hunch
9. frequently-updated-machine-learning-blogs
10. Arthur Chan's Blog

Online Books

1. Neural Networks and Deep Learning
2. Deep Learning Book
3. An Introduction to Statistical Learning
4. The Elements of Statistical Learning
5. A Course in Machine Learning

Notes

1. cs229: ML Course Materials

Cheat Sheets

1. KDNuggets: data-science-machine-learning-cheat-sheets

Misc Others

1. TensorFlow
2. Tensorflow for Deep Learning Research
3. TensorFlow-Examples
4. pytorch-tutorial
5. learning-deep-learning-my-top-five-resource

Articles

Forward and Backpropagation

1. yes-you-should-understand-backprop
2. Neural Network in Python
3. Step By Step Backpropagation

RNN

1. Andrej Karpathy's lecture
2. Christopher Olah on how LSTMs work
3. RNN using TensorFlow
4. Andrej Karpathy's Blog

Useful Resources

1. Open Source Data Science Masters
2. analyticsvidhya: 21 Deep Learning Videos (2016)
3. analyticsvidhya: Top YouTube Videos (2015)
4. Free Python Books
5. 16 Free Machine Learning Books
6. frequently-updated-machine-learning-blogs

Quora

1. What-are-the-best-machine-learning-blogs-or-resources-available
2. How-do-I-learn-machine-learning-1
3. What-are-some-good-books-papers-for-learning-deep-learning

Misc

1. Visual Information Theory
2. 4 Steps for Learning Deep Learning
3. How to build a Recurrent Neural Network in TensorFlow (1/7)
4. Understanding-LSTMs
5. anyone-can-code-lstm