Designing Machine Learning Systems with Python

David Julian

商品描述

Design efficient machine learning systems that give you more accurate results

About This Book

  • Gain an understanding of the machine learning design process
  • Optimize machine learning systems for improved accuracy
  • Understand common programming tools and techniques for machine learning
  • Develop techniques and strategies for dealing with large amounts of data from a variety of sources
  • Build models to solve unique tasks

Who This Book Is For

This book is for data scientists, scientists, or just the curious. To get the most out of this book, you will need to know some linear algebra and some Python, and have a basic knowledge of machine learning concepts.

What You Will Learn

  • Gain an understanding of the machine learning design process
  • Optimize the error function of your machine learning system
  • Understand the common programming patterns used in machine learning
  • Discover optimizing techniques that will help you get the most from your data
  • Find out how to design models uniquely suited to your task

In Detail

Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles.

There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more.

Style and approach

This easy-to-follow, step-by-step guide covers the most important machine learning models and techniques from a design perspective.

商品描述(中文翻譯)

設計高效的機器學習系統,為您提供更準確的結果

關於本書
- 瞭解機器學習設計過程
- 優化機器學習系統以提高準確性
- 瞭解機器學習的常見編程工具和技術
- 開發處理來自各種來源的大量數據的技巧和策略
- 構建模型以解決獨特的任務

本書適合對數據科學家、科學家或只是好奇的人。為了充分利用本書,您需要了解一些線性代數和一些Python,並具備基本的機器學習概念知識。

您將學到什麼
- 瞭解機器學習設計過程
- 優化機器學習系統的誤差函數
- 瞭解機器學習中常用的編程模式
- 發現優化技巧,幫助您充分利用數據
- 瞭解如何設計適合您任務的模型

詳細內容
機器學習是現代計算中增長最快的趨勢之一。它在許多領域都有應用,包括經濟學、自然科學、網站開發和商業建模。為了利用這些系統的威力,實踐者必須對底層設計原則有扎實的理解。

機器學習模型可能無法提供準確的結果有很多原因。通過從設計的角度來看待這些系統,我們可以更深入地了解底層算法和可用的優化方法。本書將為您提供機器學習設計過程的堅實基礎,並使您能夠構建定制的機器學習模型來解決獨特的問題。您可能已經了解或使用過一些現成的機器學習模型來解決常見問題,如垃圾郵件檢測或電影分類,但要開始解決更複雜的問題,將這些模型適應您自己的特定需求非常重要。本書將為您提供這種理解和更多。

風格和方法
這本易於跟隨的逐步指南從設計的角度介紹了最重要的機器學習模型和技術。