# Resources for Data Science Interviews

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:
- MIT 18.06 Linear Algebra with Gilbert Strang
- MIT 18.S096 Topics in Math… Finance
- Econometrics 421

- Books:
- No B.S. Guide to Linear Algebra

- FastAi
- Computational Linear Algebra Course https://github.com/fastai/numerical-linear-algebra

### Computer Science

- YouTube:
- MIT 6.006 Intro to Algorithms
- Khan Academy Algorithms

- Udacity:
- Data Structures and Algorithms
- Intro to Algorithms

- Books:
- Think Complexity
- Crack the Coding Interview

### NLP

- YouTube:
- Stanford CS 224N

- Books:
- Natural Language Processing with PyTorch

#### Deep Learning and ML Stuff

- Books:
- Hands on Machine Learning with SciKit-Learn and Tensorflow
- Data Science from Scratch
- Deep Learning
- Elegant SciPy
- Data Science at the Command Line

- Udacity:
- Deep Learning Nanodegree

- Udemy:
- PyTorch for Deep Learning

### Data Science Periphery

- Books:
- Docker for Data Science
- Apache Spark: The Definitive Guide
- Kafka: The Definitive Guide
- Kubernetes Up and Running

- Udemy:
- The Ultimate Hands On Guide to Hadoop
- Build a SaaS app in Flask

### Learning R for Pythonistas

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

Written on January 2, 2020