Machine Learning Cookbook

Atul Tripathi

  • 出版商: Packt Publishing
  • 出版日期: 2017-03-24
  • 定價: $1,980
  • 售價: 6.0$1,188
  • 語言: 英文
  • 頁數: 570
  • 裝訂: Paperback
  • ISBN: 1785280511
  • ISBN-13: 9781785280511
  • 相關分類: Machine Learning
  • 相關翻譯: 機器學習實踐指南 (簡中版)
  • 立即出貨 (庫存=1)

商品描述

Key Features

  • This book will show you how to improve the efficiency of your systems
  • Improve predictions and recommendations to have better levels of accuracy
  • Optimize performance of your Machine learning systems

Book Description

Machine learning (ML) became the new black and is in constant demand by many organizations who work with huge amounts of data all the time. The complexity of finding, understanding, and predicting outcomes makes ML very difficult. This cookbook will solve the everyday difficulties and struggles you face as a data scientist. As a concept, machine learning has a single goal for data scientists to achieve-predictive analytics, but to reach that goal, data scientists have to be prepared for all types of data, no matter how good or bad. This is the focus of the book.

As you already know about machine learning techniques with specific languages or tools, we'll show you how to improve the efficiency of your systems so your predictions and recommendations have better levels of accuracy and better performance.

The first half of the book provides recipes on a fairly complex machine learning systems where you'll learn to improve its efficiency. That includes recipes on: classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more.

The second half of the book focuses on three different ML case studies all based on real-world data and offer solutions and solve specifics ML issues in each one.

What you will learn

  • Get equipped with a deeper understanding of how to apply machine learning techniques
  • Implement each of the advanced machine learning techniques
  • Solve real-life problems that are encountered in order to make your applications produce improved results
  • Gain hands-on experience of problem solving for your Machine learning systems
  • Understand the methods of collecting data, preparing data for usage, training the model, evaluating the model's performance, and improving the model's performance

商品描述(中文翻譯)

《主要特點》
- 本書將向您展示如何提高系統的效率
- 提高預測和推薦的準確性水平
- 優化機器學習系統的性能

《書籍描述》
機器學習(ML)已成為許多組織不斷需求的熱門領域,這些組織一直在處理大量的數據。找到、理解和預測結果的複雜性使得機器學習變得非常困難。這本食譜將解決您作為數據科學家所面臨的日常困難和挑戰。作為一個概念,機器學習對於數據科學家來說有一個目標-預測分析,但要達到這個目標,數據科學家必須為各種類型的數據做好準備,無論好壞。這是本書的重點。

由於您已經了解特定語言或工具的機器學習技術,我們將向您展示如何提高系統的效率,以便您的預測和推薦具有更高的準確性和更好的性能。

本書的前半部分提供了一些相當複雜的機器學習系統的食譜,您將學習如何提高其效率。這包括分類、神經網絡、無監督和監督學習、深度學習、強化學習等食譜。

本書的後半部分聚焦於三個不同的機器學習案例研究,都基於真實世界的數據,並提供解決方案,解決每個案例中的特定機器學習問題。

《您將學到什麼》
- 獲得更深入的了解如何應用機器學習技術
- 實施每一種高級機器學習技術
- 解決實際問題,以使您的應用程序產生改進的結果
- 獲得解決機器學習系統問題的實踐經驗
- 了解數據收集、數據準備、模型訓練、模型性能評估和模型性能改進的方法