Are you starting your data science journey? There are lots of ways to learn like Udemy courses and YouTube videos, but staying organized and motivated is the key. We are here to share five books that cover the basics of data science, from Python to statistics, making your learning easier.
Python: A Whirlwind Tour of Python
If you want a quick start with Python, this book is perfect. It explains Python’s basics like numbers and words and introduces important tools like NumPy and Pandas.
Statistics: Think Stats: Probability and Statistics for Programmers
This book focuses on key statistics concepts and includes practical exercises in Python. You will learn about summary statistics, probability distributions, hypothesis testing and more.
Linear Algebra: Introduction to Linear Algebra for Applied Machine Learning with Python
Linear algebra can be daunting, but this book simplifies it. It introduces you to the fundamentals of linear algebra, which is crucial for understanding machine learning. Each theoretical concept is followed by practical examples using the NumPy library.
Machine Learning: Introduction to Machine Learning with Python
Once you are comfortable with Python, stats and math, it is time for machine learning. This beginner-friendly book uses a tool called scikit-learn and explains different machine tricks like linear stuff, decision trees and support vectors.
Deep Learning: Deep Learning with Python
This book is for those who already know something about Python and want to want to know much more without having any prior machine learning experience. It explains important things like neural networks, special networks for pictures and networks that make new stuff.
These five book suggestions are great for those who are just starting a journey in data science. These are simultaneously of good help to experienced data experts and researchers who look ahead to brush up on important ideas.
