MATLAB Machine Learning Recipes: A Problem-Solution Approach, 2/e (Paperback)

Michael Paluszek, Stephanie Thomas

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商品描述

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem.
 
All code in MATLAB Machine Learning Recipes:  A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more.
 
What you'll learn:
  • How to write code for machine learning, adaptive control and estimation using MATLAB
  • How these three areas complement each other
  • How these three areas are needed for robust machine learning applications
  • How to use MATLAB graphics and visualization tools for machine learning
  • How to code real world examples in MATLAB for major applications of machine learning in big data
 
Who is this book for:

 

The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.
 

商品描述(中文翻譯)

利用MATLAB的強大功能來解決各種機器學習挑戰。本書提供了一系列關鍵於機器學習的技術範例,每個範例都解決了一個現實世界的問題。

《MATLAB機器學習食譜:問題解決方法》中的所有代碼都是可執行的。該代碼使用的工具箱提供了實現機器學習各個方面所需的完整功能集。作者Michael Paluszek和Stephanie Thomas展示了所有這些技術如何讓讀者能夠構建複雜的應用程序,解決模式識別、自動駕駛、專家系統等問題。

你將學到什麼:
- 如何使用MATLAB編寫機器學習、自適應控制和估計的代碼
- 這三個領域如何相互補充
- 這三個領域在強大的機器學習應用中的必要性
- 如何使用MATLAB圖形和可視化工具進行機器學習
- 如何在MATLAB中編寫大數據機器學習主要應用的現實世界範例

這本書適合的讀者:
主要面向工程師、數據科學家和學生,他們希望通過使用MATLAB進行機器學習來獲得一本豐富範例的綜合代碼手冊。