New lecture on recent developments in deep learning is defined in the state of the art in our field (algorithms, applications, and tools). This is a complete list, but hopefully 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-dee ... 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 & OpenI 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
Source: https://www.youtube.com/watch?v=53YvP6gdD7U (Accessed on January 22, 2019)
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