本文内容整理自MIT教育视频，讲解的是近两年来深度学习一些方面最现今的进展，类似于综述。本文将列举出内容的纲要，视频连接资源和PPT资源下载链接。

视频的纲要

Deep Learning: State of the Art*
(Breakthrough Developments in 2017 & 2018)

• BERT and Natural Language Processing
• Tesla Autopilot Hardware v2+: Neural Networks at Scale
• AdaNet: AutoML with Ensembles
• AutoAugment: Deep RL Data Augmentation
• Training Deep Networks with Synthetic Data
• Segmentation Annotation with Polygon-RNN++
• DAWNBench: Training Fast and Cheap
• BigGAN: State of the Art in Image Synthesis
• Video-to-Video Synthesis
• Semantic Segmentation
• AlphaZero & OpenAI Five
• Deep Learning Frameworks

This is not a list of state-of-the-art results on main machine learning benchmark datasets. It’s an overview of exciting recent developments.

PPT链接下载地址: https://pan.baidu.com/s/1KTge6ByMnMwP4jo-dLIRnw

MIT学校官网视频（应该不需翻墙）：https://deeplearning.mit.edu/

视频链接（需翻墙）：https://www.youtube.com/watch?v=53YvP6gdD7U

相关视频播放列表（需翻墙）：https://www.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

在Github中的教程（推荐）：https://github.com/lexfridman/mit-deep-learning

其他第三方的整理，里面包含视频，推荐：https://mp.weixin.qq.com/s/cGKsZYxrVP7hVnv7Jli9Zg