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kmario23 / deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
https://deep-learning-drizzle.github.io
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New lectures #43

Closed tathaghosh closed 4 years ago

tathaghosh commented 4 years ago

  1. Deep Learning for Computer Vision (Fall 2019) https://web.eecs.umich.edu/~justincj/teaching/eecs498/ http://leccap.engin.umich.edu/leccap/site/jhygcph151x25gjj1f0

  2. Designing, Visualizing and Understanding Deep Neural Networks (Spring 2020) https://bcourses.berkeley.edu/courses/1487769/pages/cs-l-w-182-slash-282a-designing-visualizing-and-understanding-deep-neural-networks-spring-2020 https://www.youtube.com/playlist?list=PLkFD6_40KJIwaO6Eca8kzsEFBob0nFvwm

  3. DEEP LEARNING (DS-GA 1008 · SPRING 2020) https://atcold.github.io/pytorch-Deep-Learning/ https://www.youtube.com/playlist?list=PLLHTzKZzVU9eaEyErdV26ikyolxOsz6mq

  4. CS165: Foundations of Machine Learning and Statistical Inference http://tensorlab.cms.caltech.edu/users/anima/cms165-2020.html https://www.youtube.com/user/msagopa/videos

mzahran001 commented 4 years ago
  1. CS 330: Deep Multi-Task and Meta-Learning https://cs330.stanford.edu/ https://www.youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5
mzahran001 commented 4 years ago
  1. CS294-158-SP20 Deep Unsupervised Learning Spring 2020 https://sites.google.com/view/berkeley-cs294-158-sp20/home https://www.youtube.com/playlist?list=PLwRJQ4m4UJjPiJP3691u-qWwPGVKzSlNP
mzahran001 commented 4 years ago
  1. CS 188 | Introduction to Artificial Intelligence https://inst.eecs.berkeley.edu/~cs188/fa18/ https://www.youtube.com/playlist?list=PL7k0r4t5c108AZRwfW-FhnkZ0sCKBChLH
mzahran001 commented 4 years ago

  1. CS221: Artificial Intelligence: Principles and Techniques https://stanford-cs221.github.io/autumn2019/ https://www.youtube.com/playlist?list=PLoROMvodv4rO1NB9TD4iUZ3qghGEGtqNX

  2. CPSC 322: Introduction to Artificial Intelligence (UBC) https://www.youtube.com/playlist?list=PLDPnGbm0sUmpzvcGvktbz446SLdFbfZVU

mzahran001 commented 4 years ago

  1. Machine Learning 10-601, Spring 2015 Carnegie Mellon University http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml

  2. Probabilistic Graphical Models Spring 2019 Carnegie Mellon University https://sailinglab.github.io/pgm-spring-2019/lectures/ https://www.youtube.com/playlist?list=PLoZgVqqHOumTY2CAQHL45tQp6kmDnDcqn

  3. Probabilistic Graphical Models Spring 2020 Carnegie Mellon University https://www.cs.cmu.edu/~epxing/Class/10708-20/lectures.html https://www.youtube.com/playlist?list=PLoZgVqqHOumTqxIhcdcpOAJOOimrRCGZn

  4. 11-785 Introduction to Deep Learning Spring 2020 Carnegie Mellon University https://deeplearning.cs.cmu.edu/ https://www.youtube.com/playlist?list=PLp-0K3kfddPzCnS4CqKphh-zT3aDwybDe

  5. 11-785 Introduction to Deep Learning Spring 2019 Carnegie Mellon University https://www.cs.cmu.edu/~bhiksha/courses/deeplearning/Spring.2019/www/ https://www.youtube.com/playlist?list=PLp-0K3kfddPwz13VqV1PaMXF6V6dYdEsj

  6. Convex Optimization: Fall 2018 Carnegie Mellon University https://www.stat.cmu.edu/~ryantibs/convexopt-F18/

  7. Convex Optimization: Fall 2015 Carnegie Mellon University stat.cmu.edu/~ryantibs/convexopt-F15/

  8. Convex Optimization: Spring 2015 Carnegie Mellon University https://www.stat.cmu.edu/~ryantibs/convexopt-S15/

  9. Convex Optimization: Fall 2016 Carnegie Mellon University https://www.stat.cmu.edu/~ryantibs/convexopt-F16/

  10. Statistical Machine Learning: Spring 2017 https://www.stat.cmu.edu/~ryantibs/statml/

  11. 10-725 Optimization Fall 2012 Carnegie Mellon University https://www.youtube.com/playlist?list=PL7y-1rk2cCsDOv91McLOnV4kExFfTB7dU

  12. 10-606 and 10-607 Math Background for ML, Fall 2017 https://canvas.cmu.edu/courses/603/assignments/syllabus https://www.youtube.com/playlist?list=PL7y-1rk2cCsAqRtWoZ95z-GMcecVG5mzA

  13. Advanced Introduction to Machine Learning 10-715 Carnegie Mellon University https://www.cs.cmu.edu/~bapoczos/Classes/ML10715_2015Fall/ https://www.youtube.com/playlist?list=PL4YhK0pT0ZhWBzSBkMGzpnPw6sf6Ma0IX

mzahran001 commented 4 years ago

  1. 15-780 Graduate Artificial Intelligence | CMU https://www.youtube.com/playlist?list=PL_Ig1a5kxu55zgIn3Tb5Pc5C62Yo2sYHf http://www.cs.cmu.edu/~arielpro/15780s18/index.html

  2. CMU 10-605 Machine Learning With Large Datasets https://www.youtube.com/playlist?list=PLnfBqXRW5MRhPtfkadfwQ0VcuSi2IwEcW

kmario23 commented 4 years ago
  1. Deep Learning for Computer Vision (Fall 2019) https://web.eecs.umich.edu/~justincj/teaching/eecs498/ http://leccap.engin.umich.edu/leccap/site/jhygcph151x25gjj1f0
  2. Designing, Visualizing and Understanding Deep Neural Networks (Spring 2020) https://bcourses.berkeley.edu/courses/1487769/pages/cs-l-w-182-slash-282a-designing-visualizing-and-understanding-deep-neural-networks-spring-2020 https://www.youtube.com/playlist?list=PLkFD6_40KJIwaO6Eca8kzsEFBob0nFvwm
  3. DEEP LEARNING (DS-GA 1008 · SPRING 2020) https://atcold.github.io/pytorch-Deep-Learning/ https://www.youtube.com/playlist?list=PLLHTzKZzVU9eaEyErdV26ikyolxOsz6mq
  4. CS165: Foundations of Machine Learning and Statistical Inference http://tensorlab.cms.caltech.edu/users/anima/cms165-2020.html https://www.youtube.com/user/msagopa/videos

@tathatj thanks a bunch!! Updated all of these. I've been traveling, hence the delay.

kmario23 commented 4 years ago
  1. Machine Learning 10-601, Spring 2015 Carnegie Mellon University http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml
  2. Probabilistic Graphical Models Spring 2019 Carnegie Mellon University https://sailinglab.github.io/pgm-spring-2019/lectures/ https://www.youtube.com/playlist?list=PLoZgVqqHOumTY2CAQHL45tQp6kmDnDcqn
  3. Probabilistic Graphical Models Spring 2020 Carnegie Mellon University https://www.cs.cmu.edu/~epxing/Class/10708-20/lectures.html https://www.youtube.com/playlist?list=PLoZgVqqHOumTqxIhcdcpOAJOOimrRCGZn
  4. 11-785 Introduction to Deep Learning Spring 2020 Carnegie Mellon University https://deeplearning.cs.cmu.edu/ https://www.youtube.com/playlist?list=PLp-0K3kfddPzCnS4CqKphh-zT3aDwybDe
  5. 11-785 Introduction to Deep Learning Spring 2019 Carnegie Mellon University https://www.cs.cmu.edu/~bhiksha/courses/deeplearning/Spring.2019/www/ https://www.youtube.com/playlist?list=PLp-0K3kfddPwz13VqV1PaMXF6V6dYdEsj
  6. Convex Optimization: Fall 2018 Carnegie Mellon University https://www.stat.cmu.edu/~ryantibs/convexopt-F18/
  7. Convex Optimization: Fall 2015 Carnegie Mellon University stat.cmu.edu/~ryantibs/convexopt-F15/
  8. Convex Optimization: Spring 2015 Carnegie Mellon University https://www.stat.cmu.edu/~ryantibs/convexopt-S15/
  9. Convex Optimization: Fall 2016 Carnegie Mellon University https://www.stat.cmu.edu/~ryantibs/convexopt-F16/
  10. Statistical Machine Learning: Spring 2017 https://www.stat.cmu.edu/~ryantibs/statml/
  11. 10-725 Optimization Fall 2012 Carnegie Mellon University https://www.youtube.com/playlist?list=PL7y-1rk2cCsDOv91McLOnV4kExFfTB7dU
  12. 10-606 and 10-607 Math Background for ML, Fall 2017 https://canvas.cmu.edu/courses/603/assignments/syllabus https://www.youtube.com/playlist?list=PL7y-1rk2cCsAqRtWoZ95z-GMcecVG5mzA
  13. Advanced Introduction to Machine Learning 10-715 Carnegie Mellon University https://www.cs.cmu.edu/~bapoczos/Classes/ML10715_2015Fall/ https://www.youtube.com/playlist?list=PL4YhK0pT0ZhWBzSBkMGzpnPw6sf6Ma0IX

Hey @mo-zahran, thanks a lot for putting effort with this!! Really appreciated :) I have added all of these except for general AI courses. Since I was unsure about the category, I've left it for now..