My curated list on How to Learn Deep Learning

Different courses teach the same thing from different point of view. Learning it from different point of views make your knowledge well rounded. Even though it is repetitative, it helps.

Suggested Libraries to master, in increasing order of complexity

  1. Keras
    • Very Easy to understand
    • Functions are implemented already
  2. Tensorflow or Pytorch (choose one)
    1. Tensorflow
      • Made for production
      • Not as easy as Pytorch but catching up
    2. Pytorch
      • Not as wide support for production as Tensorflow but catching up
      • Easier to learn than Tensorflow

Level 1 Basic with Keras: Deep Learning Basic

  1. Mooc - Udemy: Deep Learning with Python and Keras
  2. Mooc - Udemy: https://www.udemy.com/course/complete-tensorflow-2-and-keras-deep-learning-bootcamp/ (Skip Tensorflow in the Beginning)
  3. Book: Deep Learning with Keras by Francois Chollet
  4. Mooc - Fast AI: Practical Deep Learning for Coders
  5. Mooc: AI for Everyone by Andrew Ng
  6. Mooc: A Crash Course in Data Science by Johns Hopkins University

Level 2 Basic with Tensorflow: Deep Learning Intermediate

  1. Mooc - Udemy: Complete Guide to TensorFlow for Deep Learning with Python
  2. Mooc - Udemy: Tensorflow 2.0: Deep Learning and Artificial Intelligence
  3. Mooc - Udemy: Complete Tensorflow 2 and Keras Deep Learning Bootcamp
  4. Mooc - Coursera: TensorFlow in Practice Specialization
  5. Mooc - Coursera: Getting Started with Tensorflow 2.0

Level 3 Advanced Tensorflow: Deep Learning Advanced

  1. Book: TensorFlow for Deep Learning by Bharath Ramsundar
  2. Book: Grokking Deep Learning by Andrew Trask