找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Neural Networks and Deep Learning; A Textbook Charu C. Aggarwal Textbook 20181st edition Springer International Publishing AG, part of Spri

[復制鏈接]
查看: 34697|回復: 43
樓主
發(fā)表于 2025-3-21 17:53:57 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Neural Networks and Deep Learning
副標題A Textbook
編輯Charu C. Aggarwal
視頻videohttp://file.papertrans.cn/664/663704/663704.mp4
概述This book covers the theory and algorithms of deep learning and it provides detailed discussions of the relationships of neural networks with traditional machine learning algorithms..The mathematical
圖書封面Titlebook: Neural Networks and Deep Learning; A Textbook Charu C. Aggarwal Textbook 20181st edition Springer International Publishing AG, part of Spri
描述.This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book? is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered.?The chapters of this book span three categories:..The basics of neural networks: .?Many traditional machine learning models can be understood as special cases of neural networks.? An emphasis is placed in the first two chapters on understanding the relationship between traditio
出版日期Textbook 20181st edition
關鍵詞Deep Learning; Machine Learning; Radial Basis Function Networks; Restricted Boltzmann Machines; Recurren
版次1
doihttps://doi.org/10.1007/978-3-319-94463-0
isbn_softcover978-3-030-06856-1
isbn_ebook978-3-319-94463-0
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

書目名稱Neural Networks and Deep Learning影響因子(影響力)




書目名稱Neural Networks and Deep Learning影響因子(影響力)學科排名




書目名稱Neural Networks and Deep Learning網(wǎng)絡公開度




書目名稱Neural Networks and Deep Learning網(wǎng)絡公開度學科排名




書目名稱Neural Networks and Deep Learning被引頻次




書目名稱Neural Networks and Deep Learning被引頻次學科排名




書目名稱Neural Networks and Deep Learning年度引用




書目名稱Neural Networks and Deep Learning年度引用學科排名




書目名稱Neural Networks and Deep Learning讀者反饋




書目名稱Neural Networks and Deep Learning讀者反饋學科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒有投票權限
沙發(fā)
發(fā)表于 2025-3-21 21:24:20 | 只看該作者
板凳
發(fā)表于 2025-3-22 02:21:54 | 只看該作者
An Introduction to Neural Networks,n axons and dendrites are referred to as .. These connections are illustrated in Figure?.(a). The strengths of synaptic connections often change in response to external stimuli. This change is how learning takes place in living organisms.
地板
發(fā)表于 2025-3-22 07:40:22 | 只看該作者
Convolutional Neural Networks,al locations in an image often have similar color values of the individual pixels. An additional dimension captures the different colors, which creates a 3-dimensional input .. Therefore, the features in a convolutional neural network have dependencies among one another based on spatial distances.
5#
發(fā)表于 2025-3-22 10:31:06 | 只看該作者
An Introduction to Neural Networks,system contains cells, which are referred to as .. The neurons are connected to one another with the use of . and ., and the connecting regions between axons and dendrites are referred to as .. These connections are illustrated in Figure?.(a). The strengths of synaptic connections often change in re
6#
發(fā)表于 2025-3-22 15:43:52 | 只看該作者
7#
發(fā)表于 2025-3-22 19:11:36 | 只看該作者
8#
發(fā)表于 2025-3-22 22:46:42 | 只看該作者
9#
發(fā)表于 2025-3-23 03:27:50 | 只看該作者
10#
發(fā)表于 2025-3-23 08:31:21 | 只看該作者
Charu C. Aggarwalthe General Motors Research Laboratories on September 25-27, 1983. This was the 28th syposium in aseries which the Research Laboratories began sponsor- ing in 1957. Each symposium has focused on a topic that is both under active study at the Research Laboratories and is also of interest to the large
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-10 13:06
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
喀什市| 夏河县| 滁州市| 青阳县| 婺源县| 新田县| 绍兴市| 绍兴县| 祁连县| 章丘市| 苏尼特左旗| 辰溪县| 平谷区| 南平市| 时尚| 清徐县| 苏州市| 保山市| 金平| 长泰县| 六安市| 隆尧县| 汾阳市| 临江市| 万州区| 濮阳市| 澎湖县| 连州市| 连云港市| 大城县| 清徐县| 洪湖市| 墨竹工卡县| 正安县| 调兵山市| 高碑店市| 梁平县| 石渠县| 鄂伦春自治旗| 清河县| 焦作市|