R Machine Learning Projects: Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5

Dr. Sunil Kumar Chinnamgari

買這商品的人也買了...

商品描述

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more

Key Features

  • Master machine learning, deep learning, and predictive modeling concepts in R 3.5
  • Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains
  • Implement smart cognitive models with helpful tips and best practices

Book Description

R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization.

This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you'll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You'll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine.

By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations.

What you will learn

  • Explore deep neural networks and various frameworks that can be used in R
  • Develop a joke recommendation engine to recommend jokes that match users' tastes
  • Create powerful ML models with ensembles to predict employee attrition
  • Build autoencoders for credit card fraud detection
  • Work with image recognition and convolutional neural networks
  • Make predictions for casino slot machine using reinforcement learning
  • Implement NLP techniques for sentiment analysis and customer segmentation

Who this book is for

If you're a data analyst, data scientist, or machine learning developer who wants to master machine learning concepts using R by building real-world projects, this is the book for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this book.

Table of Contents

  1. Exploring the Machine Learning Landscape
  2. Predicting Employees Attrition using Ensemble models
  3. Implementing a Jokes Recommendation Engine
  4. Sentiment Analysis of Amazon Reviews with NLP
  5. Customer Segmentation Using Wholesale Data
  6. Image Recognition using Deep Neural Network
  7. Credit Card Fraud Detection Using Autoencoders
  8. Automatic Prose Generation with Recurrent Neural Networks
  9. Winning the Casino Slot Machine with Reinforcement Learning
  10. Appendix

商品描述(中文翻譯)

這本書的標題是「使用TensorFlow for R、H2O、MXNet等工具,通過真實世界的專案來掌握多個機器學習領域」。以下是書中的重點特色:
- 在R 3.5中掌握機器學習、深度學習和預測建模的概念
- 在金融、零售、社交媒體等不同領域中建立智能的端到端專案
- 使用實用的技巧和最佳實踐來實現智能認知模型

這本書介紹了R語言在計算統計(統計計算)和探索機器學習的數學方面時的流行程度。通過這本書,您將利用R生態系統來建立高效的機器學習應用,以執行組織內的智能任務。

這本書將幫助您測試您的知識和技能,指導您如何從簡單到複雜地建立機器學習專案。您將首先學習如何使用集成模型建立強大的機器學習模型,以預測員工流失。接下來,您將實現一個笑話推薦引擎,並學習如何對亞馬遜評論進行情感分析。您還將探索不同的聚類技術,使用批發數據對客戶進行分段。此外,本書還將讓您熟悉使用自編碼器進行信用卡欺詐檢測,以及使用強化學習在賭場老虎機上進行預測和贏取遊戲。

通過閱讀本書,您將能夠自信地執行複雜任務,為自動化操作建立研究和商業專案。

您將學到以下內容:
- 探索深度神經網絡和在R中使用的各種框架
- 開發一個笑話推薦引擎,推薦符合用戶口味的笑話
- 使用集成模型建立強大的機器學習模型,以預測員工流失
- 使用自編碼器進行信用卡欺詐檢測
- 使用圖像識別和卷積神經網絡
- 使用強化學習對賭場老虎機進行預測
- 實施自然語言處理技術進行情感分析和客戶分段

這本書適合數據分析師、數據科學家或機器學習開發人員,他們希望通過建立真實世界的專案來掌握使用R進行機器學習的概念。每個專案都將幫助您測試實施機器學習算法和技術的能力。為了充分利用本書,需要基本的機器學習理解和R編程的工作知識。

本書的目錄如下:
1. 探索機器學習領域
2. 使用集成模型預測員工流失
3. 實現笑話推薦引擎
4. 使用自然語言處理對亞馬遜評論進行情感分析
5. 使用批發數據進行客戶分段
6. 使用深度神經網絡進行圖像識別
7. 使用自編碼器進行信用卡欺詐檢測
8. 使用循環神經網絡進行自動散文生成
9. 使用強化學習贏得賭場老虎機
10. 附錄