Neural Networks and Deep Learning: Deep Learning explained to your granny

Pat Nakamoto

  • 出版商: CreateSpace Independent Publishing Platform
  • 出版日期: 2017-12-05
  • 售價: $1,063
  • 貴賓價: 9.5$1,010
  • 語言: 英文
  • 頁數: 130
  • 裝訂: Paperback
  • ISBN: 1981614060
  • ISBN-13: 9781981614066
  • 相關分類: Machine LearningDeepLearning
  • 立即出貨(限量) (庫存=1)



Ready to crank up a neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning’ to your LinkedIn profile? Well, hold on there... Before you embark on your epic journey into the world of deep learning, there is basic theory to march through first! Take a step-by-step journey through the basics of Neural Networks and Deep Learning, made so simple that…even your granny could understand it! What you will gain from this book: * A deep understanding of how a Neural Network and Deep Learning work * A basics comprehension on how to build a Deep Neural Network from scratch Who this book is for: * Beginners who want to approach the topic, but are too afraid of complex math to start! What’s Inside? * A brief introduction to Machine Learning * Two main Types of Machine Learning Algorithms * A practical example of Unsupervised Learning * What are Neural Networks? * McCulloch-Pitts's Neuron * Types of activation function * Types of network architectures * Learning processes * Advantages and disadvantages * Let us give a memory to our Neural Network * The example of book writing Software * Deep learning: the ability of learning to learn * How does Deep Learning work? * Main architectures and algorithms * Main types of DNN * Available Frameworks and libraries * Convolutional Neural Networks * Tunnel Vision * Convolution * The right Architecture for a Neural Network * Test your Neural Network Hit download. Now!


準備好啟動神經網絡,讓你的自駕車接送孩子上學了嗎?想在 LinkedIn 上增加「深度學習」的專業技能嗎?那麼,請稍等一下... 在你踏上深度學習的史詩般旅程之前,先來了解一下基本理論吧!這本書將以簡單易懂的方式,一步一步地介紹神經網絡和深度學習的基礎知識,就連你的奶奶都能理解!閱讀本書,你將獲得以下收穫: * 深入了解神經網絡和深度學習的工作原理 * 掌握從頭開始構建深度神經網絡的基礎知識 本書適合對這個主題感興趣但害怕複雜數學的初學者!內容包括: * 機器學習簡介 * 兩種主要的機器學習算法 * 一個實際的無監督學習示例 * 什麼是神經網絡? * McCulloch-Pitts 神經元 * 激活函數的類型 * 網絡架構的類型 * 學習過程 * 優點和缺點 * 讓我們的神經網絡有記憶 * 書寫軟件的示例 * 深度學習:學習學習的能力 * 深度學習的工作原理 * 主要的架構和算法 * 主要的深度神經網絡類型 * 可用的框架和庫 * 卷積神經網絡 * 隧道視覺 * 卷積 * 適合神經網絡的正確架構 * 測試你的神經網絡 立即下載!