Machine Learning Resources!

Hi! This thread is for all the machine learning resources out there, Feel free to add yours by commenting here.

Let me start by giving some:
Books

  1. Mathematics for Machine Learning
  2. Machine Learning
  3. Probablistic approach to machine learning by Kevin Murphy

Research Papers

  1. https://paperswithcode.com/

Hands-On GitHub Repos for ML(TF & Scikit, PyTorch):

1)GitHub - ageron/handson-ml2: A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
2)GitHub - rasbt/python-machine-learning-book-2nd-edition: The "Python Machine Learning (2nd edition)" book code repository and info resource
3) GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.

Good Courses online :

  1. Fast.ai
  2. Production level ML → https://fullstackdeeplearning.com/
  3. Mathematics in Machine Learning Specialization on coursera by ICL → https://www.coursera.org/specializations/mathematics-machine-learning (If you can’t pay, please ask for financial aid in the link)
  4. Deep learning book by LEGENDS(Turing Award Winner Yoshua Bengio & Ian Goodfellow): http://www.deeplearningbook.org/
  5. Intel’s Course: https://software.intel.com/en-us/ai/courses
  6. Nvidia’s course: https://www.nvidia.com/en-us/deep-learning-ai/education/
  7. www.Udacity.com → Alot of free courses( do not look for nanodegrees)
  8. https://www.coursera.org/specializations/deep-learning → Andrew Ng’s new Deep learning course
  9. https://dlrlsummerschool.ca/past-years/

Websites

  1. https://madewithml.com/
  2. 10-301 + 10-601, Spring 2021

Tools

  1. Weights and Biases (Visualize your DNN Progress etc.)
  2. Streamlit (Manages frontend)
  3. Microsoft NNI (AutoML)
  4. OpenAI Gym and MuJoCo(Environment Creator and Gym for Reinforcement learning)
  5. rapids.ai
  6. Sklearn, Tensorflow, Keras, PyTorch

Data Visualization Resources

  1. SandDance

Fun Noobish Things you might want to know about:

  1. https://teachablemachine.withgoogle.com/
  2. https://sketch2code.azurewebsites.net/

Amazing Blogs

  1. pudding.cool
  2. https://www.ailab.microsoft.com/experiments/30c61484-d081-4072-99d6-e132d362b99d
  3. Data project checklist · fast.ai

Famous Conferences:

  1. NeurIPS(formerly NIPS)
  2. AAAI
  3. AIES

Reinforcement Learning Resources

  1. Lil'Log
  2. Welcome to Spinning Up in Deep RL! — Spinning Up documentation
  3. https://cmudeeprl.github.io/703website/

All the best on your machine learning journey~

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