Data Science Books 📚 you should start reading
🧵👇
🧵👇
1. Data Science from Scratch
You’ll learn how many of the most fundamental DS tools and algorithms work by implementing them from scratch. Includes:
- Python basics
- Linear algebra, statistics, & probability
- Data collection & EDA
- Basic ML Algo
learning.oreilly.com/library/view/d…
You’ll learn how many of the most fundamental DS tools and algorithms work by implementing them from scratch. Includes:
- Python basics
- Linear algebra, statistics, & probability
- Data collection & EDA
- Basic ML Algo
learning.oreilly.com/library/view/d…
2. Python for Data Analysis
This book deals with manipulating, processing, cleaning, and crunching data in Python. It is about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems.
learning.oreilly.com/library/view/p…
This book deals with manipulating, processing, cleaning, and crunching data in Python. It is about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems.
learning.oreilly.com/library/view/p…
3. Introduction to Machine Learning with Python
If you're completely new to ML and want to learn it from 0 then this book is for you. You’ll learn the steps necessary to create a successful ML application with Python and the Scikit-learn library.
learning.oreilly.com/library/view/i…
If you're completely new to ML and want to learn it from 0 then this book is for you. You’ll learn the steps necessary to create a successful ML application with Python and the Scikit-learn library.
learning.oreilly.com/library/view/i…
4. Machine Learning with Python Cookbook
It provides 200 recipes to help you solve ML challenges you may face in your daily work. You’ll learn about loading data, handling text or numerical data, model selection, dimensionality reduction, & many more.
learning.oreilly.com/library/view/m…
It provides 200 recipes to help you solve ML challenges you may face in your daily work. You’ll learn about loading data, handling text or numerical data, model selection, dimensionality reduction, & many more.
learning.oreilly.com/library/view/m…
5. Hands-On Machine Learning with Scikit-Learn, Keras, & TensorFlow
You’ll learn a range of techniques, starting with linear regression & progressing to deep neural networks. There are exercises in each chapter to help you apply what you’ve learned
learning.oreilly.com/library/view/h…
You’ll learn a range of techniques, starting with linear regression & progressing to deep neural networks. There are exercises in each chapter to help you apply what you’ve learned
learning.oreilly.com/library/view/h…
6. An Introduction to Statistical Learning
Awesome book for understanding the mathematics behind ML & analyzing the different types of data. It is written in extremely simple language & no very complex mathematics terms are used.
statlearning.com
Awesome book for understanding the mathematics behind ML & analyzing the different types of data. It is written in extremely simple language & no very complex mathematics terms are used.
statlearning.com
7. Mathematics for Machine Learning
This book provides great coverage of all the basic mathematical concepts for machine learning.
mml-book.github.io
This book provides great coverage of all the basic mathematical concepts for machine learning.
mml-book.github.io
8. The Hundred-Page Machine Learning Book
Great for those looking for a refresher of ML concepts before interviews.
themlbook.com
Great for those looking for a refresher of ML concepts before interviews.
themlbook.com
9. Build a Career in Data Science
Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager.
manning.com/books/build-a-…
Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager.
manning.com/books/build-a-…
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Please do add if you feel I have missed something!
A retweet for the first one would really mean a lot 🙏
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