Street Coder (Manning)
Friday, 25 February 2022

This book, subtitled "The rules to break and how to break them", looks at how computer science theory quickly collides with the harsh reality of professional software development. in this smart and funny beginner's guide, Sedat Kapanoglu shows you how to get the job done by prioritizing tasks, making quick decisions, and knowing which rules to break. This is a programmer's survival guide, full of tips, tricks, and hacks that will make you a more efficient programmer. It takes the best practices you learn in a computer science class and deconstructs them to show when they’re beneficial—and when they aren't!

<ASIN:1617298379>

 

Author: Sedat Kapanoglu
Publisher: Manning
Date: February 2022
Pages: 272
ISBN: 978-1617298370
Print: 1617298379
Kindle: B09Q3PJQC5
Audience: General
Level: Introductory/Intermediate
Category: Theory & Techniques 

streetcoder

 

  • Beginner-friendly insights on code optimization, parallelization, and refactoring
  • Put “bad” practices to good use
  • Learn to love testing
  • Embrace code breaks and become friends with failure

 

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.

 

 

Banner
 


Deep Learning (No Starch Press)

Author: Andrew Glassner
Publisher: No Starch Press
Date: July 2021
Pages: 750
ISBN: 978-1718500723
Print: 1718500726
Kindle: ‎ B085BVWXNS
Audience: Developers interested in deep learning
Rating: Mike James
Reviewer: 5
A book on deep learning wtihout an equation in sight?



Machine Learning with PyTorch and Scikit-Learn

Author: Sebastian Raschka, Yuxi (Hayden) Liu & Vahid Mirjalili
Publisher: Packt
Date: February 2022
Pages: 770
ISBN: 978-1801819312
Print: 1801819319
Kindle: B09NW48MR1
Audience: Python developers interested in machine learning
Rating: 5
Reviewer: Mike James
This is a very big book of machine le [ ... ]


More Reviews