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: Deep Learning Models; A Practical Approach Jonah Gamba Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license t

[復(fù)制鏈接]
樓主: 萬能
21#
發(fā)表于 2025-3-25 03:35:43 | 只看該作者
Remote Sensing Example for Deep Learning, neural networks. However, there is an increasing recognition that deep learning, which has been?applied successfully in other areas such as computer vision and language processing, is a viable alternative to traditional machine learning. This chapter will work through a specific example of the?appl
22#
發(fā)表于 2025-3-25 09:29:56 | 只看該作者
23#
發(fā)表于 2025-3-25 13:37:16 | 只看該作者
https://doi.org/10.1007/978-3-030-96866-3reader a big picture of the position of deep learning and how it evolved. The scope of this book is given at the end of the chapter. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide?a list of references for further reading.
24#
發(fā)表于 2025-3-25 18:19:28 | 只看該作者
Basic Approaches in Object Detection and Classification by Deep Learning,reader a big picture of the position of deep learning and how it evolved. The scope of this book is given at the end of the chapter. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide?a list of references for further reading.
25#
發(fā)表于 2025-3-25 20:14:11 | 只看該作者
https://doi.org/10.1007/978-3-031-45319-9er that we give a quick dive into the Keras library and some references for further investigation. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide a?list of references for further reading.
26#
發(fā)表于 2025-3-26 02:28:48 | 只看該作者
https://doi.org/10.1007/978-3-031-45319-9e of deep learning models given a set of data. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide a?list of references for further reading.
27#
發(fā)表于 2025-3-26 07:06:20 | 只看該作者
28#
發(fā)表于 2025-3-26 12:08:57 | 只看該作者
The Building Blocks of Machine Learning and Deep Learning,e of deep learning models given a set of data. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide a?list of references for further reading.
29#
發(fā)表于 2025-3-26 12:59:33 | 只看該作者
30#
發(fā)表于 2025-3-26 20:10:05 | 只看該作者
 關(guān)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(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-23 02:10
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
和硕县| 社会| 广宗县| 塔河县| 山西省| 德安县| 上饶市| 麻栗坡县| 小金县| 乡城县| 天等县| 美姑县| 昭苏县| 紫金县| 灵山县| 麻城市| 巫山县| 榆中县| 惠水县| 卢氏县| 丽水市| 南陵县| 旅游| 三亚市| 仙游县| 鹤庆县| 枣阳市| 东丰县| 安乡县| 赣榆县| 凯里市| 桐乡市| 炎陵县| 临泉县| 石嘴山市| 南雄市| 寻甸| 资兴市| 肥东县| 杭州市| 阳信县|