Machine Learning Mastery With Python: Understand Your Data, Create Accurate Models, and Work Projects End-to-End

by Jason Brownlee

The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this Ebook, learn exactly how to get started and apply machine learning using the Python ecosystem.

Genres: Computer Science, Academic, Technology, Artificial Intelligence

178 pages, ebook

Published January 1, 2016

About the author

Jason Brownlee, Ph.D. trained and worked as a research scientist and software engineer for many years (e.g. enterprise, R&D, and scientific computing), and is known online for his work on Computational Intelligence (e.g. Clever Algorithms), Machine Learning and Deep Learning (e.g. Machine Learning Mastery, sold in 2021) and Python Concurrency (e.g. Super Fast Python).

Jason writes fiction under the pseudonym J.D. Brownlee: https://www.goodreads.com/jdbrownlee

Reviews

[Aimee · Rating 5 out of 5]

Jason's books and website tutorials are always awesome and so helpful.

[Tolu Andre Olatunbosun · Rating 4 out of 5]

Pretty solid cookbook to get people started with grabbing datasets, and applying them into his pre-made code/tutorials. I'll be rifling through his other books when I get the chance but I was satisfied with this read.

[Ahmed · Rating 3 out of 5]

مش كتاب نظري، فلو عايز تفاصيل رياضية، منصحش بيا. لكن لمستوي للمبتدئين و المتوسطين اللي عايزين يشتغلوا عملي ويطلّعوا نماذج كويسة .
في الفصل 18 زي خريطة لأي مشروع جاي، وفيه نصايح عن تظبيط الموديلات والمجموعات وحفظ نتايج التدريب النموذج في نهاية المشروع

It's not a theoretical book, so if you're looking for mathematical details, I wouldn't recommend it. But for beginners and intermediate learners who want to work practically and build good models, it's a great fit.

Chapter 18 serves as a roadmap for any upcoming project, offering tips on fine-tuning models, managing datasets, and saving the trained model results at the end of the project.

[Alireza Aghamohammadi · Rating 2 out of 5]

کتاب با استفاده از زبان برنامه‌نویسی پایتون و کتابخانه sklearn مدل‌های یادگیری ماشین را آموزش می‌دهد.
در کل من چندان نپسندیدم. دانش جدیدی به شما نسبت به خود مستند کتابخانه sklearn اضافه نمی‌کند.
تنها میزیت‌اش سادگی و دسته‌بندی مطالب است.

[Prateek Sinha · Rating 3 out of 5]

Only good for basic python code for data science

[Jahioj · Rating 2 out of 5]

N

[Joshua Laferriere · Rating 4 out of 5]

covers the essentials, but I can tell the author is piece mealing his offerings

[Saruul · Rating 5 out of 5]

Very nice intuitive explanations and it comes with Python codes! Definitely a book to keep on my bookshelf.