Please recommend some popular science machine learning zero-based introduction

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Please recommend some popular science machine learning zero-based introduction [Copy link]

 

Please recommend some popular science machine learning zero-based introduction

何包蛋

Here are some machine learning resources for beginners:

1. "The Road to Machine Learning: An Engineer's Self-Taught Journey" : The author of this book is a person who taught himself machine learning from scratch and became a professional engineer. The book records his learning experience and methods in detail, and is suitable for reference for beginners with zero foundation.

2. "Practical Machine Learning" : This book provides many practical cases and leads readers to understand the basic principles and applications of machine learning through practical projects. It is a good choice for getting started with machine learning.

3. "Python Basic Machine Learning Tutorial" : This book uses Python as the programming language to introduce the basic theories and common algorithms of machine learning, and helps readers get started quickly through simple and easy-to-understand examples.

4. "Practical Machine Learning: Based on Scikit-Learn and TensorFlow" : This book takes practical projects as the main line and teaches you step by step how to use tools such as Scikit-Learn and TensorFlow to implement machine learning projects. It is suitable for beginners with zero foundation.

5. Machine Learning Course on Coursera : Andrew Ng’s Machine Learning course is one of the most popular introductory courses on Coursera. It is suitable for beginners with zero foundation. Through this course, you can systematically learn the basic theories and algorithms of machine learning.

6. Machine learning tutorials on YouTube : There are many high-quality machine learning tutorials on YouTube, such as Sentdex's tutorials, 3Blue1Brown's tutorials, etc. These videos are usually vivid and suitable for beginners with zero basic knowledge.

I hope the above resources can help you get started with machine learning quickly!

会飞的笨鱼

Here are some popular science books on machine learning that are suitable for beginners:

1. "Python Programming from Entry to Practice" (Author: Eric Matthes) :

   • This book is an introductory book on Python programming for beginners, suitable for readers with zero basic knowledge. The book introduces the basic knowledge and skills of Python programming, and provides a large number of example codes and project cases to help readers quickly master Python programming.

2. "In-depth and Easy Data Analysis" (Author: Wei Yuqi) :

   • This book introduces the basic concepts, methods and techniques of data analysis, and is suitable for readers with no basic knowledge. The content of the book is easy to understand, and it helps readers understand the core ideas and application methods of data analysis through rich cases and examples.

3. "Machine Learning White Book" (Author: Li Hang) :

   • This is an introductory book that introduces the basics of machine learning and is suitable for readers with no basic knowledge. The content of the book is concise and clear, focusing on the basic concepts, common algorithms and application scenarios of machine learning. It is a good starting point for learning machine learning.

4. "Statistical Learning Methods" (Author: Li Hang) :

   • This book is a classic machine learning textbook that introduces the basic theories and methods of statistical learning. Although the content is relatively in-depth, the author introduces the basic principles and algorithms of machine learning in easy-to-understand language, which is suitable for readers with zero basics to get started.

These books are introductory popular science books on machine learning for readers with no basic knowledge. By reading these books, you can build an understanding of the basic concepts of machine learning and understand the application scenarios and methods of machine learning.

大头玩家

For electronic engineers who are new to machine learning, here are some recommended resources:

1. Machine Learning Yearning : This book written by Andrew Ng is not a typical technical guide, but a guide on how to formulate and manage machine learning projects. It is very helpful for understanding the basic principles and processes of machine learning projects.

2. "Hands-on Deep Learning" : This book provides the basic concepts and practices of deep learning, suitable for readers with zero foundation. The book covers everything from basic linear regression to deep learning, and provides a large number of code examples and practical projects.

3. Tutorial videos on YouTube : There are many popular science videos on machine learning on YouTube, such as 3Blue1Brown's neural network series, CrashCourse's artificial intelligence series, etc. These videos are easy to understand and suitable for readers with zero foundation to quickly understand the basic concepts of machine learning.

4. Coursera courses : Coursera offers some introductory courses on machine learning provided by well-known universities and institutions, such as Andrew Ng's "Machine Learning" course. These courses usually start from the basics to explain the principles and applications of machine learning, and are suitable for readers with zero basics.

5. Kaggle Kernels : Kaggle offers many machine learning-based projects and competitions where you can find various practical projects and learn other people's codes and techniques.

The above are some popular science resources suitable for beginners of machine learning. I hope they are helpful to you!

fjdeepblue

Very good information, the summary is very detailed and valuable for reference, thank you for sharing