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

⬆️ YOLOv7

YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Github: https://github.com/wongkinyiu/yolov7

Paper: https://arxiv.org/abs/2207.02696v1

Dataset: https://paperswithcode.com/dataset/coco

BOOK
High-Dimensional Data Analysis with Low-Dimensional Models:
Principles, Computation, and Applications
John Wright and Yi Ma
Cambridge University Press
https://book-wright-ma.github.io/