Data Science from Scratch

Data Science from Scratch First Principles with Python

Data science libraries, frameworks, modules, and toolkits are great for data science, but they're also a great way to immerse yourself in the discipline without really understanding data science. In this updated second edition, learn how many of the most basic data science algorithms and tools work when you implement them from scratch.

Data Science from Scratch PDF

As someone who teaches tutorials as a part-time job, I'd say implementing matrix operations in a neural network tutorial is overkill. No matter what level the tutorial is at, you should always draw a line and assume a certain amount of prior knowledge and knowing how to use standard tools is not too much to ask. (Yes, I know that numpy is not part of the standard Python library, but it comes with almost all Python distributions, as many other libraries depend on it.)

If you have a knack for math and some programming skills, author Joel Grus will help you familiarize yourself with the math and statistics at the core of data science, as well as the hacking skills you need to get started as a data scientist. . Today's chaotic flood of data contains answers to questions no one wanted to ask. This book will give you the knowledge you need to find these answers.

Feel free to PM if you need more specific recommendations as it was really difficult to make a concise list. I have seen many friends and colleagues struggle with certain popular books. Sometimes it's okay that you don't like the way someone writes, even if they're really smart and super famous.