On whence someone asked me “now that I am finished with class, what books should I read and videos should I watch in order to learn more about this field?” and I answered “get ready to drink from the firehose.”

Data Science Resources

In no particular order but the math is the most helpful

Stats

• If you haven’t already read ISLR, start there. Book Link
• Practical Statistics for Data Science Amazon Link

Linear Algebra

• Udacity’s Linear Algebra Refresher
• YouTube:
  1. MIT 18.06 Linear Algebra with Gilbert Strang
  2. MIT 18.S096 Topics in Math… Finance
  3. Econometrics 421
• Books:
  1. No B.S. Guide to Linear Algebra
• FastAi
  1. Computational Linear Algebra Course https://github.com/fastai/numerical-linear-algebra

Computer Science

• YouTube:
  1. MIT 6.006 Intro to Algorithms
  2. Khan Academy Algorithms
• Udacity:
  1. Data Structures and Algorithms
  2. Intro to Algorithms
• Books:
  1. Think Complexity
  2. Crack the Coding Interview

NLP

• YouTube:
  1. Stanford CS 224N
• Books:
  1. Natural Language Processing with PyTorch

Deep Learning and ML Stuff

• Books:
  1. Hands on Machine Learning with SciKit-Learn and Tensorflow
  2. Data Science from Scratch
  3. Deep Learning
  4. Elegant SciPy
  5. Data Science at the Command Line
• Udacity:
  1. Deep Learning Nanodegree
• Udemy:
  1. PyTorch for Deep Learning

Data Science Periphery

• Books:
  1. Docker for Data Science
  2. Apache Spark: The Definitive Guide
  3. Kafka: The Definitive Guide
  4. Kubernetes Up and Running
• Udemy:
  1. The Ultimate Hands On Guide to Hadoop
  2. Build a SaaS app in Flask

Learning R for Pythonistas

https://r4ds.had.co.nz/