- Home
- Computers
- Programming Languages
- Grokking Machine Learning, Second Edition
Grokking Machine Learning, Second Edition
List Price:
$59.99
| Expected release date is Sep 29th 2026 |
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Author:
Luis Serrano
Format:
Paperback
Pages:
525
Publisher:
Manning (September 29, 2026)
Imprint:
Manning
Release Date:
September 29, 2026
Language:
English
ISBN-13:
9781633434547
ISBN-10:
1633434540
Weight:
22.16oz
Dimensions:
7.375" x 9.25"
File:
Eloquence-SimonSchuster_04142026_P9955637_onix30-20260414.xml
List Price:
$59.99
Pub Discount:
37
As low as:
$56.99
Publisher Identifier:
P-SS
Discount Code:
H
Folder:
Eloquence
Overview
Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
Machine Learning (ML) is a broad term for software that can spot patterns in data and make decisions without being explicitly programmed for each task. ML algorithms power the search and recommendation systems, business workflows, and software security systems you use every day—including AI tools like ChatGPT. This unique book brings the core ideas of ML to life with vivid examples, engaging exercises, and crisp illustrations. There’s no jargon or complex academic theory. All you need is basic programming knowledge, high school mathematics, and curiosity!
This book helps you build an intuitive understanding of machine learning from the ground up. Each chapter introduces a core ML concept, such as regression and tree-based methods, data preprocessing, feature engineering, neural networks, and more. This totally-revised second edition also illuminates modern AI, including transformers, LLMs, and image generation models. You’ll especially appreciate the easy-to-follow Python-based exercises and hands-on mini-projects that encourage you to practice as you learn.
What's inside
• Clear code examples and fun illustrations
• How ML and AI modes are built, trained, and evaluated
• Neural networks, regression, and probabilistic models
• Data preprocessing and feature engineering
• Generative AI basics clearly explained
About the reader
For readers who know basic Python. No machine learning knowledge is necessary.
About the author
Luis G. Serrano is an artificial intelligence scientist, educator, and popularizer. Previously, he was a Machine Learning Engineer at Google and Lead Artificial Intelligence Educator at Apple.
Machine Learning (ML) is a broad term for software that can spot patterns in data and make decisions without being explicitly programmed for each task. ML algorithms power the search and recommendation systems, business workflows, and software security systems you use every day—including AI tools like ChatGPT. This unique book brings the core ideas of ML to life with vivid examples, engaging exercises, and crisp illustrations. There’s no jargon or complex academic theory. All you need is basic programming knowledge, high school mathematics, and curiosity!
This book helps you build an intuitive understanding of machine learning from the ground up. Each chapter introduces a core ML concept, such as regression and tree-based methods, data preprocessing, feature engineering, neural networks, and more. This totally-revised second edition also illuminates modern AI, including transformers, LLMs, and image generation models. You’ll especially appreciate the easy-to-follow Python-based exercises and hands-on mini-projects that encourage you to practice as you learn.
What's inside
• Clear code examples and fun illustrations
• How ML and AI modes are built, trained, and evaluated
• Neural networks, regression, and probabilistic models
• Data preprocessing and feature engineering
• Generative AI basics clearly explained
About the reader
For readers who know basic Python. No machine learning knowledge is necessary.
About the author
Luis G. Serrano is an artificial intelligence scientist, educator, and popularizer. Previously, he was a Machine Learning Engineer at Google and Lead Artificial Intelligence Educator at Apple.
