1.Understanding Convolution Neural network, Link: https://cs.stanford.edu/people/karpathy/convnetjs/index.html

2. OpenAI spinning up, a deep reinforcement learning resource. Link: https://spinningup.openai.com/en/latest/

3. BOOK: Deep learning, MIT press, author: Goodfellow and Bengio and Courville. Link: https://www.deeplearningbook.org/ 

4. Neural network Playground, learn about neural network workflow, Click on link: Link

5. Deep dreams visuals by Google, Link: https://github.com/google/deepdream/blob/master/dream.ipynb

6. Tensorflow Tutorials: Link: https://www.tensorflow.org/tutorials

7. Book: Intro to statistical Learning, Link: http://www-bcf.usc.edu/~gareth/ISL/

8. Book: The Elements of  statistical Learning, Link: https://web.stanford.edu/~hastie/ElemStatLearn/

8. Book: Natural Language Processing with Python, nltk book, Link: https://www.nltk.org/book/

9. Artificial Intelligence: A modern Approach, resources, Link: http://aima.cs.berkeley.edu/

10. Project Tuva: Richard Feynman’s Messenger Lecture Series, Microsoft, Link: https://www.microsoft.com/en-us/research/project/tuva-richard-feynman/

11.  The Feynman Lecture on Physics, Link: http://www.feynmanlectures.caltech.edu/