Deep Learning: Practical Neural Networks with Java

Yusuke Sugomori, Bostjan Kaluza, Fabio M. Soares, Alan M. F. Souza

  • 出版商: Packt Publishing
  • 出版日期: 2017-06-14
  • 定價: $2,680
  • 售價: 8.0$2,144
  • 語言: 英文
  • 頁數: 744
  • 裝訂: Paperback
  • ISBN: 1788470311
  • ISBN-13: 9781788470315
  • 相關分類: Java 程式語言DeepLearning
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商品描述

Build and run intelligent applications by leveraging key Java machine learning libraries

About This Book

  • Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries.
  • Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications
  • This step-by-step guide will help you solve real-world problems and links neural network theory to their application

Who This Book Is For

This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life.

What You Will Learn

  • Get a practical deep dive into machine learning and deep learning algorithms
  • Explore neural networks using some of the most popular Deep Learning frameworks
  • Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms
  • Apply machine learning to fraud, anomaly, and outlier detection
  • Experiment with deep learning concepts, algorithms, and the toolbox for deep learning
  • Select and split data sets into training, test, and validation, and explore validation strategies
  • Apply the code generated in practical examples, including weather forecasting and pattern recognition

In Detail

Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work.

The course provides you with highly practical content explaining deep learning with Java, from the following Packt books:

  1. Java Deep Learning Essentials
  2. Machine Learning in Java
  3. Neural Network Programming with Java, Second Edition

Style and approach

This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application

商品描述(中文翻譯)

利用主要的Java機器學習庫來建立和執行智能應用程式

關於本書


  • 使用最受歡迎的Java機器學習庫,開發解決預測建模問題的有效策略。

  • 通過圖表、原始碼和實際應用程式,探索各種數據處理、機器學習和自然語言處理。

  • 這本逐步指南將幫助您解決實際問題,並將神經網絡理論與其應用相關聯。

本書適合對象

本課程適用於數據科學家和Java開發人員,他們希望深入研究深度學習的精彩世界。它將快速讓您上手,並為您提供在現實生活中成功創建、自定義和部署機器學習應用程式所需的技能。

您將學到什麼


  • 深入了解機器學習和深度學習算法。

  • 使用一些最受歡迎的深度學習框架探索神經網絡。

  • 深入研究深度置信網絡和堆疊去噪自編碼器算法。

  • 將機器學習應用於詐騙、異常和離群值檢測。

  • 實驗深度學習概念、算法和深度學習工具箱。

  • 選擇並將數據集分為訓練、測試和驗證集,並探索驗證策略。

  • 應用在實際示例中生成的代碼,包括天氣預測和模式識別。

詳細內容

機器學習應用無處不在,從自駕車、垃圾郵件檢測、文件搜索和交易策略,到語音識別。從基本機器學習算法入門開始,本課程將帶您深入這個重要的領域,提供令人驚嘆的預測洞察和卓越的機器智能。本課程將幫助您解決圖像處理、語音識別、語言建模等具有挑戰性的問題。您將發現如何檢測異常和詐騙,以及執行活動識別、圖像識別和文本處理的方法。您還將使用天氣預測、疾病診斷、客戶分析、泛化、極端機器學習等示例進行實作。通過本課程,您將獲得在不同複雜性水平上在系統上執行深度學習所需的所有知識,並將其應用於日常工作。

本課程提供了使用Java進行深度學習的高度實用內容,來自以下Packt出版的書籍:


  1. Java深度學習基礎

  2. Java機器學習

  3. Java神經網絡編程,第二版

風格和方法

本課程旨在創建一條平滑的學習路徑,教您如何有效地使用Java進行深度學習,並與其他事實上的組件結合使用,以充分發揮其潛力。通過這個全面的課程,您將學習預測建模的基礎知識,並解決實際問題,將神經網絡理論與其應用相關聯。