Neural Networks in Unity: C# Programming for Windows 10
Abhishek Nandy
- 出版商: Apress
- 出版日期: 2018-07-15
- 售價: $1,490
- 貴賓價: 9.5 折 $1,416
- 語言: 英文
- 頁數: 172
- 裝訂: Paperback
- ISBN: 1484236726
- ISBN-13: 9781484236727
-
相關分類:
C#、遊戲引擎 Game-engine
海外代購書籍(需單獨結帳)
買這商品的人也買了...
-
$1,840$1,748 -
$2,620$2,489 -
$750$638 -
$480$379 -
$454ROS 機器人編程實踐 (Programming Robots with ROS: A Practical Introduction to the Robot Operating Syste)
-
$990Unity 2017 Game AI Programming, Third Edition
-
$403游戲 UI 設計 : 修煉之道
-
$2,205TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
-
$650$585 -
$500$390 -
$680$578 -
$520$411
相關主題
商品描述
Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform. In this book you will start by exploring back propagation and unsupervised neural networks with Unity and C#. You’ll then move onto activation functions, such as sigmoid functions, step functions, and so on. The author also explains all the variations of neural networks such as feed forward, recurrent, and radial.
Once you’ve gained the basics, you’ll start programming Unity with C#. In this section the author discusses constructing neural networks for unsupervised learning, representing a neural network in terms of data structures in C#, and replicating a neural network in Unity as a simulation. Finally, you’ll define back propagation with Unity C#, before compiling your project.
What You'll Learn
- Discover the concepts behind neural networks
- Work with Unity and C#
- See the difference between fully connected and convolutional neural networks
- Master neural network processing for Windows 10 UWP
Who This Book Is For
Gaming professionals, machine learning and deep learning enthusiasts.
商品描述(中文翻譯)
學習神經網絡的核心概念,並使用Unity作為平台。在這本書中,您將從使用Unity和C#探索反向傳播和無監督神經網絡開始。然後,您將進一步研究激活函數,例如sigmoid函數,step函數等等。作者還解釋了所有神經網絡的變體,如前饋、循環和放射性神經網絡。
一旦掌握了基礎知識,您將開始使用C#編程Unity。在這一部分中,作者討論了為無監督學習構建神經網絡,以C#中的數據結構表示神經網絡,並在Unity中模擬複製神經網絡。最後,您將使用Unity C#定義反向傳播,然後編譯您的項目。
您將學到什麼:
- 探索神經網絡的概念
- 使用Unity和C#進行工作
- 看到完全連接和卷積神經網絡之間的區別
- 掌握Windows 10 UWP的神經網絡處理
適合閱讀對象:
- 遊戲專業人士
- 機器學習和深度學習愛好者