Andrej Karpathy from Tesla is talking about Vision only autonomous driving.
https://www.youtube.com/watch?v=NSDTZQdo6H8&ab_channel=YarrowB.

Explaining Deep Neural Networks

Oana-Maria Camburu: https://arxiv.org/abs/2010.01496

#ArtificialIntelligence #DeepLearning #NeuralNetworks

As part of the Turing Lecture series for ACM's flagship publication, 2018 Turing Award laureates Yoshua Bengio, Yann Lecun, and Geoffrey Hinton discuss the current challenges and the future of deep learning: https://cacm.acm.org/magazines/2021/7/253464-deep-learning-for-ai/fulltext#R70
To watch the video: https://vimeo.com/user4730653

Physics-based Deep Learning

Thuerey et al.: https://arxiv.org/abs/2109.05237

#MachineLearning #DeepLearning #Physics

YOLOP: You Only Look Once for Panoptic Driving Perception

Wu et al.: https://arxiv.org/abs/2108.11250

#ArtificialIntelligence #DeepLearning #MachineLearning

2021 DeepMind x UCL Reinforcement Learning Lecture Series
Taught by DeepMind researchers, this series was created in collaboration with University College London (UCL) to offer students a comprehensive introduction to modern reinforcement learning.
Playlist
https://youtube.com/playlist?list=PLki3HkfgNEsKiZXMoYlR-14r1t_MAS7M8
https://youtu.be/_DpLWBG_nvk
#MachineLearning #artificialintelligence #deeplearning #computervision #MontrealAI

COURSE
Introduction to Deep Learning (I2DL) (IN2346)
Lecturer: Prof. Dr. Matthias Niessner
TUM Visual Computing Group
https://niessner.github.io/I2DL/

This is the AI event of the year!

🎉🎉 Super excited to hear from the world's top experts on AI and Machine Learning including:

→ Andrew Ng - Founder of DeepLearning.AI and Founder & CEO of LANDING AI
→ Ilya Sutskever - Co-Founder and Chief Scientist at OpenAI
→ Fei-Fei Li - Sequoia Professor of Computer Science, Stanford University & Co-Director Stanford Institute for Human-Centered Artificial Intelligence (HAI)
→ Eric Schmidt - Co-Founder Schmidt Futures, Former CEO Google
→ Kevin Scott - CTO at Microsoft


✅ Registration is free and will give you access to all recordings:
💻 https://scl.ai/3lqkK3S

How to apply machine learning from papers, guides, and interviews with ML practitioners
https://applyingml.com/

40 Open-Source Audio Datasets for ML

Over 2 TBs of labeled audio datasets publicly available and parseable on DagsHub

https://towardsdatascience.com/40-open-source-audio-datasets-for-ml-59dc39d48f06

A ConvNet for the 2020s

https://arxiv.org/abs/2201.03545

https://github.com/facebookresearch/ConvNeXt

ML YouTube Courses

collection of some of the latest machine learning / NLP courses available on YouTube.

https://github.com/dair-ai/ML-YouTube-Courses

Draft:

https://arxiv.org/pdf/2106.10165.pdf

Physics-based Deep Learning

https://physicsbaseddeeplearning.org/intro.html

https://arxiv.org/pdf/2109.05237.pdf

MLOPS Course
https://github.com/GokuMohandas/MLOps