Grokking Machine Learning: A Gentle Introduction for Software Engineers and Data Scientists
What is Grokking Machine Learning?
Groking Machine Learning is a book that teaches the fundamentals of machine learning in a way that is accessible to software engineers and data scientists. The book is written by Andrew Ng, a professor at Stanford University and one of the leading experts in machine learning, and Pete Warden, a former Google engineer and the founder of the machine learning company Nervana.
The book is divided into three parts. The first part covers the basics of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. The second part covers more advanced topics, such as neural networks, deep learning, and natural language processing. The third part covers the practical aspects of machine learning, such as data preprocessing, model selection, and deployment.
Grokking Machine Learning is a valuable resource for anyone who wants to learn about machine learning. The book is well-written, and it provides a comprehensive overview of the field. The exercises and examples are helpful for reinforcing the concepts that are covered in the text.
4.5 out of 5
Language | : | English |
File size | : | 18084 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 906 pages |
Screen Reader | : | Supported |
Features of Grokking Machine Learning
- Clear and concise writing style. The book is written in a clear and concise style, making it easy to understand even for beginners.
- Comprehensive coverage of machine learning. The book covers a wide range of machine learning topics, from the basics to more advanced topics.
- Practical examples and exercises. The book is packed with practical examples and exercises, which help to reinforce the concepts that are covered in the text.
- Code snippets in Python. The book includes code snippets in Python, which makes it easy to implement the machine learning algorithms that are discussed in the text.
Why Grokking Machine Learning?
There are many reasons why you should read Grokking Machine Learning.
- If you are a software engineer or data scientist, and you want to learn about machine learning, this book is a great place to start. The book provides a comprehensive overview of the field, and it is written in a clear and concise style.
- If you are already familiar with machine learning, but you want to learn more about the practical aspects of the field, this book is a valuable resource. The book covers topics such as data preprocessing, model selection, and deployment.
- If you are looking for a book that is well-written and packed with practical examples, this book is a great choice. The book is written by two experts in the field, and it is full of helpful tips and tricks.
Grokking Machine Learning is a valuable resource for anyone who wants to learn about machine learning. The book is well-written, and it provides a comprehensive overview of the field. The exercises and examples are helpful for reinforcing the concepts that are covered in the text. I highly recommend this book to anyone who is interested in learning about machine learning.
4.5 out of 5
Language | : | English |
File size | : | 18084 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 906 pages |
Screen Reader | : | Supported |
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4.5 out of 5
Language | : | English |
File size | : | 18084 KB |
Text-to-Speech | : | Enabled |
Enhanced typesetting | : | Enabled |
Print length | : | 906 pages |
Screen Reader | : | Supported |