小象学院 《深度学习》第三期价值899元-17年5月
课程名称:
《深度学习》 第三期
主讲老师：
李伟， 美国纽约城市大学博士
研究领域包括深度学习，计算机视觉，人脸计算以及人机交互，即将毕业加入美国顶级云计算平台人工智能研究组。在CVPR，ECCV等顶级会议上发表了多篇学术文章，同时他还是WACV，ACCV，ECCV等重要视觉会议以及MVA，CVIU等期刊的审稿人。
课程简介：
本次的深度学习课程主要包括三大部分：
1） 深度学习核心原理。了解深度学习运行的最核心数学原理，从而对后续的知识点扩展，模型设计与优化技能打下基础。
2） 深度学习知识点连接。会涵盖主流的深度学习研究工程应用中碰到的大部分知识点，与大部分学习资料孤立进行知识点介绍不同，会结合主讲人自身总结找到所有知识点之间的联系，便于系统掌握。
3） 介绍不同知识点的代表应用。结合所学的原理以及知识点，介绍比较重要的图像和语言方面的应用，如增强学习，迁移学习，GAN等， 方便学员针对自身兴趣的目标进行强化训练。
面向人群：
1.想了解和学习深度学习的学习者
2.想学习深度学习的相关从业人员
3.想转行从事深度的学习者
学习收益：
通过本课程的学习，学员将会收获：
1.帮助学员系统性的掌握深度学习的基本原理，以及从基本概念到各个先进模型的转化思路
2.了解研究过程中定义问题设计模型的思路
3.培养学员面对工程及学术问题的思考解决能力
4.快速积累深度学习项目经验
课程目录：
课时1：第一课_深度学习总体介绍
课时2：视频-第一课_深度学习总体介绍
课时3：第二课_传统神经网络
课时4：视频-第二课_传统神经网络
课时5：第三讲_卷积神经网络－基础篇
课时6：视频-第三讲_卷积神经网络－基础篇
课时7：第四讲_卷积神经网络－高级篇
课时8：视频-第四讲_卷积神经网络－高级篇
课时9：第五讲_卷积神经网络－目标分类
课时10：视频-第五讲_卷积神经网络－目标分类
课时11：第六讲_卷积神经网络－目标探测
课时12：视频-第六讲_卷积神经网络－目标探测
课时13：第七讲_递归神经网络
课时14：视频-第七讲_递归神经网络
课时15：第八讲_卷积网络+递归网络
课时16：视频-第八讲_卷积网络+递归网络
课时17：第九讲_生成对抗网络
课时18：视频-第九讲_生成对抗网络
课时19：第十讲_增强学习
课时20：视频-第十讲_增强学习
视频截图：
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