"Machine Learning in Action" by Peter Harrington offers a deep dive into the world of machine learning, combining theoretical knowledge with practical skills. It's the perfect source for those looking to master the fundamentals and applied aspects of machine learning.
This publication provides tools and techniques used for optimizing business processes, improving customer service, and developing new data-based products.
What's Inside the Book?
The guide unveils key concepts and algorithms of machine learning, emphasizing the practical side of the field. Peter Harrington guides readers through the primary stages of developing machine learning models, from data preprocessing to model efficiency evaluation.
A significant part of the book is devoted to code examples demonstrating the implementation of algorithms in popular programming languages. The author also touches on important topics like deep learning, neural networks, and reinforcement learning, making the material useful for a broad range of specialists.
Who Should Read "Machine Learning in Action" by Peter Harrington, Manning publications?
- Data professionals looking to expand their knowledge in machine learning.
- Software developers aiming to integrate machine learning algorithms into their projects.
- Technical students studying artificial intelligence and machine learning.
- Researchers working on artificial intelligence projects.
- Project managers and business executives wanting to understand the potential of machine learning for their business.
What Are the Advantages of This Textbook?
- Detailed explanation of the theoretical foundations of machine learning.
- A rich set of practical examples and problems.
- Updated information on the latest trends and technologies.
- Accessibility of material for readers with different levels of preparation.
- Inclusion of modern topics such as deep learning and neural networks.
- Practical advice on implementing and optimizing models.
- Demonstrations of real-world applications of machine learning.
More About the Author of the Book
The Developer's Opinion About the Book
A practical deep dive into machine learning concepts using real code and case studies. It balances theory and hands-on implementation. After reading, you’ll understand supervised learning, clustering, and model evaluation. Great for developers looking to apply ML in production settings. The book is known for translating statistical theory into clear Python code, making it a bridge between academic knowledge and applied skills.
Sarah Bennett, Machine Learning Developer
FAQ for "Machine Learning in Action"
Question 1: What style is the book written in?
Answer: It's written in an accessible, understandable style with an emphasis on practical application of knowledge. The author aims to avoid excessive theoretical complexity, focusing instead on practical examples.
Question 2: Is prior programming knowledge required to understand the material?
Answer: Yes, a basic understanding of a popular programming language, such as Python, will be a significant advantage, as many examples and tasks in the textbook are implemented using code.
Question 3: What machine learning algorithms are discussed in the guide?
Answer: The author covers a broad spectrum of algorithms, from simple methods like linear regression and classification to more complex ones such as neural networks and deep learning algorithms.
Question 4: Is "Machine Learning in Action" by Peter Harrington, Manning publications suitable for preparing for a career in data?
Answer: Absolutely, this publication will be a valuable resource for those aiming to build a career in data analysis, machine learning, or artificial intelligence.
Question 5: Are there sections in the book dedicated to practical projects?
Answer: Yes, it includes chapters focused on implementing specific machine learning projects, allowing you to apply theoretical knowledge practically.
Information
| Author: | Peter Harrington | Language: | English |
| Publisher: | Manning | ISBN-13: | 978-1617290183 |
| Publication Date: | April 19, 2012 | ISBN-10: | 9781617290183 |
| Print Length: | 384 pages | Category: | Machine Learning and Artificial Intelligence Books |
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