Learn Data Science from the Ground Up: Master the Fundamentals of Python Programming

Data Science from Scratch: First Principles with Python by Joel Grus is the perfect book for business professionals looking to gain an in-depth understanding of data science. Written in an easy-to-follow manner, this book provides a comprehensive overview of the fundamentals of data science, from the basics of Python programming to the application of statistical concepts. With a focus on knowledgeable, binding, and page quality, this book is sure to provide readers with a comprehensive understanding of data science and its applications. Additionally, overall satisfaction with this book is guaranteed due to its easy-to-read format and comprehensive coverage of the subject.

Key Features:

Scratch: Data Science From First Principles With Python is an essential guide for those looking to gain an understanding of data science. This book covers the fundamentals of data science, from basic concepts to advanced techniques, all with an emphasis on using Python. With step-by-step instructions and examples, readers will gain a comprehensive understanding of data science and be able to apply their knowledge to real-world problems. Whether you're a beginner or an experienced data scientist, this book is a must-have for anyone looking to master the fundamentals of data science.
72
B2B Rating
35 reviews

Review rating details

Value for money
85
Overall satisfaction
85
Knowledgeable
85
Easy to read
84
Binding and page quality
88

Comments

rc: I was enjoying this book until I got to the Chapters requiring use of the Scratch files. I spend hours trying to get them to work and to no avail. If you are selling a book for £30 everything should be ready to go. Scouring GitHub for information on how to use a file required by a large portion of the book is unacceptable. Returned.

United Kingdom on Sep 11, 2023

Marco: Mr. Grus' book is one of the better data science book I have set my eyes on.

His writing style is friendly and informal. Despite this he covers the mathematical and Computational topics in reasonable depth and always points to further reading at the end of chapters.

The fact that all code used in the book is also explained therein makes the algorithms very graspable.

I would recommend this book anybody who wants to either start with data science or fill in some gaps like was the case with me.

I would love read more books written by Mr. Grus'. I have become a fan.

Germany on Jul 28, 2023

CyphercraftCyphercraft: Did you see something on the news about ChatGPT, Stable Diffusion, or some other big development that made you want to look into machine learning?

Maybe you truly plan on entering data science as a field but don't know where to start?

Or perhaps you've seen one of the author's brilliant/hilarious talks about why he doesn't like Jupyter Notebooks or how to answer the infamous "FizzBuzz" programming interview question using Tensorflow neural networks (seriously, look up Joel Grus on YouTube).

If you know a little bit of Python, a little bit of relevant math, and want to go into any data science or machine learning path, then this book is a must-have. It certainly won't be the only resource you'll need, but it helps you get the most out of other content you'll likely look into later (like how to code up a machine learning pipeline, or maybe a large language model if you're really adventurous).

Far too many machine learning lessons out there just tell you to import certain Python libraries (scikit-learn for example) and start using them without giving you any basic understanding of how those imported functions even work to begin with. Even...

United States on Apr 17, 2023

KB: This book is good. Yes it’s explains from scratch and with python codes. Easy to grasp.

Mexico on Sep 03, 2022

Debora Bonini: The book is useful to grasp the basic concept behind data science. However it gets pretty messy as the topics become more complex, especially when the python code is shown without too much of explanations. If you need a book to learn python for data science, there are many other alternatives.

Italy on Oct 29, 2021

Michael Covelli: This is a great book. Doing everything from scratch and not just using numpy, sklearn, etc is a great way to learn what's really going on underneath. I'm surprised how far he gets along this path. By the end, you will have implemented a keras-like deep learning setup. It won't be fast enough for production use since it's all using Lists underneath, but you'll be able to see how it all fits together. Also, coming from a more typed language background, I loved the type annotations.

United States on Jul 28, 2021

Vaibhav gupta: Good book for someone starting on learning basics of AI/ML

United States on Dec 26, 2020

Gerardo Mazzei: Let me start this review by explaining clearly who this book is for: anyone who has had some form of introduction (even if concise) to programming in Python, algebra, statistics, and probability will find this book a great introduction to Data Science. While the author does a great job at having a crash course on these topics (and I even learned a thing or two here and there), I can see the contents being a bit overwhelming if this is your first point of contact with these subjects. However, should you meet the requirements I mentioned above, you'll find this book a breeze! Joel does a good job at explaining the topics using his signature brand of humor, keeping the read entertaining even in the most advanced areas. I'd even say that this is a must read if you are considering going into machine learning, since it teaches you a thing or two in the topic as well. Please keep in mind that the book is monochrome. If that bothers you, consider viewing the electronic version.

TLDR: If you're looking for a concise introduction to data science and have a bit of knowledge of basic Python, algebra, statistics and probability, look no further than this book!...

United States on May 15, 2020

Amazon Customer: This book is suitable for people with basic python programming skills. It is very good for beginners and advanced users alike. The codes are very clear and without errors. This book teaches you the basics and introduce some expert level topics for you to explore further if keen. If you are a novice data analyst and some harder topics throw you off, you should probably revisit the topics after you have gain more knowledge on data science.

I highly recommend this book as your first book into data science because the codes and thought processes are very clear. 70-80% of the book are data science foundation and basics for you to tackle harder topics later.

United States on Mar 17, 2020

Dragos Manailoiu: Great read if you're starting out in data science has no typos and is easy to read through
Highly recommended if that's the first book you buy

Canada on Nov 23, 2019



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