MATLAB Machine Learning Recipes: A Problem-Solution Approach, 2/e (Paperback)
Michael Paluszek, Stephanie Thomas
- 出版商: Apress
- 出版日期: 2019-02-01
- 定價: $1,480
- 售價: 5.0 折 $740
- 語言: 英文
- 頁數: 283
- 裝訂: Paperback
- ISBN: 1484239156
- ISBN-13: 9781484239155
-
相關分類:
Matlab、Machine Learning
-
相關翻譯:
MATLAB 機器學習：人工智能工程實踐, 2/e (簡中版)
-
其他版本:
MATLAB Machine Learning Recipes: A Problem-Solution Approach 3rd
買這商品的人也買了...
-
專案管理認證考題解析 — PMP、CPPM/CPMP、CPMS、ITE 甲級考試備考指南$650$514 -
黑客攻防技術寶典 ─ Web 實戰篇, 2/e$719$683 -
汪博士解讀 PMBOK 與 PMP 認證－幫助您透徹理解《PMBOK 指南》第 5 版 順利通過 PMP 考試$450$383 -
鳥哥的 Linux 私房菜－基礎學習篇, 4/e$980$647 -
Machine Learning and Medical Imaging$4,250$4,038 -
超圖解 Arduino 互動設計入門, 3/e$680$578 -
$2,538Deep Learning for Medical Image Analysis -
Visual Basic 2017 基礎必修課 (適用VB 2017/2015)$530$419 -
$806CISSP 認證考試指南, 7/e (CISSP All-in-One Exam Guide, 7/e) -
$1,050Learning Kali Linux: Security Testing, Penetration Testing, and Ethical Hacking -
滲透測試基礎教程$239$227 -
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras$1,800$1,710 -
MATLAB: A Practical Introduction to Programming and Problem Solving$2,300$2,185 -
學好跨平台網頁設計 -- HTML5、CSS3、JavaScript、jQuery 與 Bootstrap 4 超完美特訓班, 2/e$480$379 -
滲透測試 完全初學者指南$708$673 -
Tensorflow 2.0 Quick Start Guide$1,020$969 -
Deep learning 深度學習必讀 - Keras 大神帶你用 Python 實作 (Deep Learning with Python)$1,000$790 -
Hands-On Computer Vision with Tensorflow 2$1,395$1,325 -
深入淺出 PMP, 4/e (Head First PMP: A Learner's Companion to Passing the Project Management Professional Exam, 4/e)$1,200$948 -
PyTorch 自然語言處理｜以深度學習建立語言應用程式 (Natural Language Processing with PyTorch)$580$458 -
$301特徵工程入門與實踐 (Feature Engineering Made Easy) -
輕鬆學會 LINE 程式設計與 AI 聊天機器人實作開發$520$406 -
實戰人工智慧之深度強化學習｜使用 PyTorch x Python$500$395 -
Python 與 LINE Bot 機器人全面實戰特訓班 (附203分鐘影音教學/範例程式)$520$411 -
Windows Server 2019 系統與網站建置實務$620$490
相關主題
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。
