My Sincere Review on The Book "Scientific Computing with Python Second Edition" by Packt Publication

Scientific computing is at the core of many demanding fields like Machine Learning, AI, Data Science, Computer Vision, and more. When I first got introduced to the book “Scientific Computing with Python”, I quickly got excited and couldn’t wait to start exploring.?

Here, I express my point of view regarding this amazing book.

Book Name: Scientific Computing with Python Second Edition by Claus Fuhrer, Oliver Verdier, Jan Erik Solem

Official Link: https://www.packtpub.com/in/data/scientific-computing-with-python-second-edition

Disclaimer: The publisher requested that I review this book and gave me a copy. My review is 100% genuine and in no way trying to favor or tarnish the image of this book.

Overview of the book

This Python book is full of scientific computing principles, mathematic algorithms, and formulas. It introduces powerful modules such as Numpy, Pandas, SciPy, SymPy, mpi4py, Matplotlib, and many more. Each chapter ends with a handful of exercises to challenge you in your understanding of the chapter.

Who this book is for

I’ll recommend this book to anyone with a mathematical background who loves programming in Python. Also, a background in Python is a bonus as this book mostly covers higher-level details. No matter what you’ll like to become, been it a data scientist, researcher, developer, this book got you covered big time.

What I like?

• A handful of challenging exercises at the end of each chapter help to evaluate our understanding. Very few books have this.
• Mathematical symbols and formulas throughout the book and their implementation in Python.
• A lot of basic details were left out. I like this since it allows me to focus on the higher details.?
• Each chapter is short and not overwhelming. The important concepts are handled with little or no wordy sentences.
• Chapter 19(Comprehensive Examples) provides 3 long examples full of prototypes and Python code. This helps to apply scientific computing with Python in real-life situations.
• All the powerful modules introduced in this book such as Numpy, Pandas, SciPy, SymPy, mpi4py, Matplotlib were explained clearly with a lot of practical examples. Never seen before.

What I don’t like

• I’ll like to draw the attention of the readers to the code example sections. Most of the functions used in these examples that were supposed to be imported from their respective modules were not done. So, running most of the code examples without importing them yourself will raise the NameError exception.?

What I’ll like to see

• In the testing section, I will like to see testing with Pytest. Pytest is the most popular Python testing framework for unit testing. So, it will be great to cover it in the future edition of this book.

Conclusion

Thank you for your time and I hope this review will help someone out there to decide whether to go for this book or not. But if you ask me, I will say, “Go for it and rock it”.

Happy Reading and Coding!