Deep Learning State of the Art (2019) - MIT

New lecture on recent developments in deep learning that are defining the state of the art in our field (algorithms, applications, and tools). This is not a complete list, but hopefully includes a good sampling of new exciting ideas. For more lecture videos visit our website or follow code tutorials on our GitHub repo.

INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/2HiZyvP
Playlist: http://bit.ly/deep-learning-playlist

OUTLINE:
0:00 - Introduction
2:00 - BERT and Natural Language Processing
14:00 - Tesla Autopilot Hardware v2+: Neural Networks at Scale
16:25 - AdaNet: AutoML with Ensembles
18:32 - AutoAugment: Deep RL Data Augmentation
22:53 - Training Deep Networks with Synthetic Data
24:37 - Segmentation Annotation with Polygon-RNN++
26:39 - DAWNBench: Training Fast and Cheap
29:06 - BigGAN: State of the Art in Image Synthesis
30:14 - Video-to-Video Synthesis
32:12 - Semantic Segmentation
36:03 - AlphaZero & OpenAI Five
43:34 - Deep Learning Frameworks
44:40 - 2019 and beyond

CONNECT:
- If you enjoyed this video, please subscribe to this channel.
- Twitter: https://twitter.com/lexfridman
- LinkedIn: https://www.linkedin.com/in/lexfridman
- Facebook: https://www.facebook.com/lexfridman
- Instagram: https://www.instagram.com/lexfridman

Nächste Episode

S05E03 - Tomaso Poggio: Brains, Minds, and Machines | Lex Fridman Podcast #13