Books/video courses recommendation for data science related coding/machine learning/stats

Although the theory basis of my major, cognitive neuroscience, is based on psychology and biology, the skills I need to tackle with the research work of this field are most data science related. Since programming languages and data related techniques are developing with dramatically speed, staying tuned and keeping studying is a must.

Here I want to list some books/course videos that I found super helpful along my learning path.

Python

• Think Python
  • I learned Python from beginning with this book.
• Fluent Python
  • I learned many advanced skills in python from this book. Python has so many fancy functions/tricks that can be easily missed. This book help improving your codes in a more elegant and efficient way.
• Python Cookbook
  • A book with many random skills and tricks.
• Python Data Science Handbook
  • Learned Numpy, Pandas, Scikit-learn with this book.

R

• R for Data Science
  • Everything you need to know about tidyverse is here.
• Advanced R
  • Programming skills with R.
• R Graphics Cookbook
  • Fantastic book for ggplot2 lovers.
• R Packages
  • Built my first R package with this awesome book.
• blogdown: Creating Websites with R Markdown
  • Interested in building a website like this one you are looking at? Check out this book.
  • I also found Bookdown and Pagedown are so helpful.

Machine learning

• CS229: Machine Learning
  • This machine learning is provided by Andrew Ng from Stanford. Course videos can be found via Youtube. Very comprehensive introduction to the basic knowledge of machine learning.
• CS231n: Convolutional Neural Networks for Visual Recognition
  • As the course title implicates, this course is focused on how to apply CNN. In general it is quite straight forward if you have a solid knowledge base from CS229. Course videos can also be found via Youtube.
• deeplearning.ai
  • Andrew Ng also provides a series of advance deep learning course via Coursera.
• An Introduction to Statistical Learning
  • I read this book while taking the machine learning course for my Data Science Specialization at the University of Oregon. Very detailed and clear explanation for both the stats and coding of statistical learning.
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  • More advanced comparing with the previous one.

Misc

• Intro to CSS and HTML
• A practical video tutorial for Illustrator Adobe Illustrator Tutorials
• Pro Git something about version control
• Unix and Linux Visual QuickStart Guide learning a bit unix will even change your experience with your pc.
• Mumford Brain Stats Stats knowledge in neuroscience area.