Machine Learning, Learning Roadmap

Machine Learning (ML) is making computers do things that we’ve never made computers do before. If you want to do something new, not just new to you, but to the world, you can do it with ML. If you focus on change, you will get results. If you focus on results, you will never change.

Roadmap

Math (Calculus, Linear Algebra, Propability & Statistics)

• Calculus, Don't Memorize
• Caclulus, 3Blue1Brown
• Linear Algebra, 3Blue1Brown
• Statistics & Probability

Python for Data Science

• My Python learning roadmap
• NumPy, Pandas, Matplotlib
• 10 minutes to Pandas

Books:

• "Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython"
• "Python Data Science Handbook"

Machine Learning

Courses:

• Understand the difference between AI / Data Science / Machine Learning / Deep Learning
• Google's ML Crash Course - Just for fast recapping
• Top Machine Learning Courses
• How to Learn Machine Learning
• Machine Learning Course, Andrew Ng, coursera.org
  • Machine Learning Stanford Cheatsheet
• Stanford CS221: Artificial Intelligence
• Stanford CS229: Machine Learning
• Amazon Machine Learning Guide
• Krish Naik's complete ML course

Books:

• "Machine Learning Yearning" Andrew Ng - After finishing this book, you will have a deep understanding of how to set technical direction for a machine learning project.
• "Machine Learning for Humans" - All in one, very short explanation of ML
• "The Hundred-Page Machine Learning Book" Andriy Burkov
• "Machine Learning Engineering" Andriy Burkov
• "Machine Learning For Absolute Beginners" Oliver Theobald
• "The Elements Of Statistical Learning: Data Mining, Inference and Prediction"
• "AI and Machine Learning for Coders" - Laurence Moroney, deeplearning.ai TensorFlow Developer specialization instructor
• "Python Machine Learning"

Practice:

• The Mechanics of Machine Learning
• Applied Machine Learning
• Practical Machine Learning with Python
• Scikit-Learn
  • https://inria.github.io/scikit-learn-mooc/
  • https://scikit-learn.org/stable/tutorial/index.html

Deep Learning, Neural Networks

Courses:

• Deep Learning Specialization, Andrew Ng, coursera.org
• CS230: Deep Learning - A class of DL at Stanford by Andrew Ng
• MIT Deep Learning
• Krish Naik's complete DL course - In case you get stuck and don't understand the concepts try to find the easy explained video in this playlist

Books:

• "Grokking Deep Learning"
• "Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow"
• "Deep Learning with Python"
• "Deep Learning for Coders with fastai and PyTorch"
• advanced "Deep learning", MIT press, "Written by three experts in the field, Deep Learning is the only comprehensive book on the subject."

Extra:

• fast.ai
• My deep learning course notes
• Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data numpy, pandas, sklearn, ml, dl

Research

• OpenAI
• Google DeepMind
• Stanford AI Lab
• MIT AI Lab
• Google AI
• Google AI Blog
• Microsoft Research
• IBM Research

Extra

• Podcast with Andrew Ng about getting started in Deep Learning
• Andrew Ng's Machine Learning Career Advice
• Andrew Ng's Career Advice/Reading Research Papers