Add data of awesome-ml-courses

[LongfeiH]

Cautions:

Before starting the task, please refer to Add data of ML-YouTube-Courses, organize the data in the task link, Don't forget it, it's very important for data management. Furthermore before you add data, please check whether it is a course, if it is other forms of expression, such as book, tutorial, or the course has nothing to do with python, data science, machine learning, deep learning and AI, you can not add it temporarily. Please tick only the data you have added.

Task link: awesome-ml-courses

Introductory Lectures

• [ ] Machine Learning (Stanford CS229) | Course website

• [ ] Convolutional Neural Networks for Visual Recognition (Stanford CS231n) | Course website

• [ ] Introduction to Artificial Intelligence (UC Berkeley CS188) | Course website

• [ ] Applied Machine Learning 2020 (Columbia)

• [ ] Introduction to Reinforcement learning with David Silver (DeepMind) | Course website

• [ ] Natural Language Processing with Deep Learning (Stanford CS224N) | Course website

• [ ] Deep Learning - NYU - 2000 | Course website

Advanced Lectures

• [ ] Deep Unsupervised Learning (UC Berkeley CS294) | Course website

• [ ] Frontiers of Deep Learning (Simons Institute) | Course website

• [ ] New Deep Learning Techniques | Course website

• [ ] Geometry of Deep Learning (Microsoft Research) | Course website

• [ ] Deep Multi-Task and Meta Learning (Stanford CS330) | Course Website

• [ ] Mathematics of Machine Learning Summer School 2019 (University of Washington) | Course Website

• [ ] Probabilistic Graphical Models (Carneggie Mellon University) | Course Website

• [ ] Probabilistic and Statistical Machine Learning 2020 (University of Tübingen)

• [ ] Statistical Machine Learning 2020 (University of Tübingen)

• [ ] Mobile Sensing and Robotics 2019 (Bonn University)

• [ ] Sensors and State Estimation Course 2020 (Bonn University)

• [ ] Photogrammetry 2015 (Bonn University)

• [ ] Advanced Deep Learning & Reinforcement Learning 2020 (DeepMind / UCL)

• [ ] Data-Driven Dynamical Systems with Machine Learning

• [ ] Data-Driven Control with Machine Learning

• [ ] ECE AI Seminar Series 2020 (NYU)

• [ ] CS287 Advanced Robotics at UC Berkeley Fall 2019

• [ ] CSEP 546 - Machine Learning (AU 2019) (U of Washington)

• [ ] Deep Reinforcment Learning, Decision Making and Control (UC Berkeley CS285)

• [ ] Stanford Convex Optimization

• [ ] Stanford CS224U: Natural Language Understanding | Spring 2019

• [ ] Full Stack Deep Learning 2019

• [ ] Emerging Challenges in Deep Learning

• [ ] Deep|Bayes 2019 Summer School

• [ ] CMU Neural Nets for NLP 2020

• [ ] New Directions in Reinforcement Learning and Control (Institure for Advanced Study)

• [ ] Workshop on Theory of Deep Learning: Where next (Institure for Advanced Study)

• [ ] Deep Learning: Alchemy or Science? (Institure for Advanced Study)

• [ ] Theoretical Machine Learning Lecture Series (Institure for Advanced Study)

• [ ] Mathematics of Big Data and Machine Learning (MIT)

• [ ] Introduction to Data-Centric AI (MIT) | Lecture videos | Lab assignments