kmario23 / deep-learning-drizzle Goto Github PK

Hi~

The 6.S191 is recently updated (2021 version). They have new videos available.

1.Speech Recognition - https://www.youtube.com/channel/UCHk6uq1Cr9J3k5KNmIsYUNw/videos
2.Numerical Optimization - https://www.youtube.com/playlist?list=PL6EA0722B99332589
3.Machine Learning for Structured Data-https://www.youtube.com/playlist?list=PL4CxkUJbvNVihRKP4bXufvRLIWzeS-ieP
4.Machine Intelligence-https://www.youtube.com/playlist?list=PL4upCU5bnihwCX93Gv6AQnKmVMwx4AZoT
5.Advanced Machine Learning-https://www.cs.cornell.edu/courses/cs6780/2019sp/

I've been absolutely loving an ongoing version of Deep Learning course by Prof. Roger Grosse at Toronto. Course contents are online here: http://www.cs.toronto.edu/~rgrosse/courses/csc421_2019/
Would be a great addition to the list.

Maybe create a separate section on Transformers (in your to-do list). Recently, they have been getting a lot of attention.

https://sites.wustl.edu/jeffheaton/t81-558/

Course Name: DS-GA 1013/Math-GA 2824: Mathematical Tools for Data Science, 2021.
Instructor: Carlos Fernandez-Granda, NYU.
Course WebPage: https://cds.nyu.edu/math-tools/
Lecture Videos: https://www.youtube.com/playlist?list=PLBEf5mJtE6KtU6YlXFZD6lyYcHhW5pIlc
Year: 2021

Deep Unsupervised Learning Course from Berkeley : https://sites.google.com/view/berkeley-cs294-158-sp20/home

You can create a new section for Unsupervised learning or add it to the deep learning section.

MIT 6.S897 Machine Learning for Healthcare, Spring 2019
View the complete course: https://ocw.mit.edu/6-S897S19

https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j

CMU has uploaded a new PGM course in 2019 by Eric Xing. Highly recommended! link: https://sailinglab.github.io/pgm-spring-2019/

Add the following link for the Tableau Dashboard:

https://www.hashtagtechgeek.com/2019/10/250-machine-learning-deep-learning-videos-courseware.html

Hello, first of all, I want to thank for all the info linked on this thread.
I found this guy on youtube who has a lot of playlist and courses about the machine and deep learning.

and other things too, but not related.

1. https://www.youtube.com/watch?v=OGxgnH8y2NM&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v
2. https://www.youtube.com/watch?v=wQ8BIBpya2k&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN
3. https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL
4. https://www.youtube.com/watch?v=URTZ2jKCgBc&list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3
5. https://www.youtube.com/watch?v=v_L9jR8P-54&list=PLQVvvaa0QuDe6ZBtkCNWNUbdaBo2vA4RO
6. https://www.youtube.com/watch?v=yMk_XtIEzH8&list=PLQVvvaa0QuDezJFIOU5wDdfy4e9vdnx-7
7. https://www.youtube.com/watch?v=v3LJ6VvpfgI&list=PLQVvvaa0QuDcT3tPehHdisGMc8TInNqdq
8. https://www.youtube.com/watch?v=v_L9jR8P-54&list=PLQVvvaa0QuDe6ZBtkCNWNUbdaBo2vA4RO

Also, I want to suggest that you can put a brief introduction of what is and the purpose of each method to guide the people to go directly to what they want even if we don´t know what of these methods can be used to solve a specific problem.

Best

Discussed in #67

Request - To add courses relevant to MLOps

Course Name: CS 685: Advanced Natural Language Processing, Fall 2020.
Instructor: Mohit Iyyer, UMass.
Course WebPage: https://people.cs.umass.edu/~miyyer/cs685/index.html
Lecture Videos: https://www.youtube.com/playlist?list=PLWnsVgP6CzadmQX6qevbar3_vDBioWHJL
Year: Fall, 2020

fast.ai v3, DL, with part 2 coming, although part 1 covers a lot of topic;
Introduction to Machine Learning for Coders, ML.

This course is by CMU. It has a 2018 edition and an ongoing 2019 edition.
The lectures are here.
The course website is here.

Amazing job on doing this, I would also suggest you expand this on CV and NLP, like make separate tables for them as well, I'd be happy to help you find relevant resources for all of them. Could become a one-stop place for finding online DL lectures.

Great Job.

There are too many courses on the list, a rating on each course will help much people.

We can use github issues to rate each course.

1)Machine Learning for Signal Processing
http://home.iitk.ac.in/~vipular/stuff/2019_MLSP.html
2)Deep Learning Foundations and Applications
http://www.facweb.iitkgp.ac.in/~debdoot/courses/AI61002/Spr2020/
https://www.youtube.com/playlist?list=PL_AdDfjIMo6pZfwjZ0rJlkE_MIsmRW7Mh

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

Hi! In , if the singal lstm is replaced with Bi-LSTM,
how can Backward layer in Bi-LSTM be implemented by the lstmcell?

Most important of all, How do the outputs of Forward layer and Backward layer connected correctly?

Look forward for your suggestions. Best wishes.

I'd include Daphne Koller's course on Probabilistic Graphical Models. There currently isn't anything from a probabilistic perspective in the ML section, so definitely worth including.

The course website for the NN course is https://www.cs.toronto.edu/~hinton/coursera_lectures.html

CAP5415 Computer Vision - Fall 2020
https://www.youtube.com/playlist?list=PLd3hlSJsX_Ikm5il1HgmDB_z62BeoikFX
https://www.crcv.ucf.edu/courses/cap5415-fall-2020/

http://www.lithoguru.com/scientist/statistics/course.html

Please change the playlist link of "Uncertainty Modelling in AI" by NUS to the official link.
Official Link: https://www.youtube.com/playlist?list=PLxg0CGqViygOb9Eyc8IXM27doxjp2SK0H

1.Deep Learning for Computer Vision
https://www.youtube.com/playlist?list=PLyqSpQzTE6M_PI-rIz4O1jEgffhJU9GgG
https://onlinecourses.nptel.ac.in/noc20_cs88/preview
https://nptel.ac.in/courses/106/106/106106224/

2.CAP5415 Computer Vision - Fall 2020
https://www.youtube.com/playlist?list=PLd3hlSJsX_Ikm5il1HgmDB_z62BeoikFX
https://www.crcv.ucf.edu/courses/cap5415-fall-2020/

3.UvA - Machine Learning 1
https://www.youtube.com/playlist?list=PL8FnQMH2k7jzhtVYbKmvrMyXDYMmgjj_n
https://uvaml1.github.io/

4.Reliable and Interpretable Artificial Intelligence (2020)
https://www.youtube.com/playlist?list=PLWjm4hHpaNg6c-W7JjNYDEC_kJK9oSp0Y
https://www.sri.inf.ethz.ch/teaching/riai2020

5.CSE 291D/234 Data Systems for Machine Learning
https://www.youtube.com/playlist?list=PLXq1U9RxZE5qjvs2Fa11Chqj8RZ-rTXMn
https://cseweb.ucsd.edu/classes/fa20/cse291-d/

6.EN 601.468/668 Machine Translation Fall 2020
https://www.youtube.com/playlist?list=PLQrCiUDqDLG0lQX54o9jB4phJ-SLI6ZBQ
http://mt-class.org/jhu/

7.Machine Learning for Graphs and Sequential Data (MLGS)
https://www.in.tum.de/daml/teaching/mlgs/

8.CS5340 Uncertainty Modelling in AI
https://www.youtube.com/playlist?list=PL6liSIqFR4BXwM5xzZpRBUD8PWqSXaPpN
https://nusmods.com/modules/CS5340/uncertainty-modelling-in-ai

9.ECE 417: Multimedia Signal Processing (Fall 2020)
https://mediaspace.illinois.edu/channel/ECE%20417/26816181
https://courses.engr.illinois.edu/ece417/fa2020/

10.Optimization Methods for Machine Learning and Engineering (KIT Winter Term 20/21)
https://www.youtube.com/playlist?list=PLdkTDauaUnQpzuOCZyUUZc0lxf4-PXNR5

11.Optimization Algorithms
https://www.youtube.com/playlist?list=PLXsmhnDvpjORzPelSDs0LSDrfJcqyLlZc

First of I want to start by saying this is an amazing compilation.I recently came across this course by Joseph Redmon(Famous For Darknet framework and his amusing resume),

Playlist
https://www.youtube.com/watch?v=8jXIAWg_yHU&list=PLjMXczUzEYcHvw5YYSU92WrY8IwhTuq7p

CoursePage
https://pjreddie.com/courses/computer-vision/

It seemed to cover some awesome aspects of computer vision. Thought it might be cool to add to this compilation.

Topics in Deep Learning | Ruslan Salakhutdinov, CMU Youtube Lectures link shows playlist is unavailable.

The SP21 deep learning course is up here: https://www.youtube.com/playlist?list=PLLHTzKZzVU9e6xUfG10TkTWApKSZCzuBI

Could this be added as well? Thanks

CS285: Deep Reinforcement Learning, UC Berkeley | Fall 2019
Lecture Series, YouTube: https://www.youtube.com/playlist?list=PLkFD6_40KJIwhWJpGazJ9VSj9CFMkb79A

https://www.youtube.com/watch?v=3F-gGLSLYi0

Stanford NLP 2019 edition.
https://www.youtube.com/playlist?list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z&fbclid=IwAR2f5afK7gZkP98Zlw06P7lN1OkqwV4FC7Xu0g38Y4oetiiThZJf8j8k348

Summer School
http://videolectures.net/DLRLsummerschool2018_toronto/
http://videolectures.net/deeplearning2017_montreal/

Finally, i think you could start adding links of conference videos, like workshops or invited talks.
For example, https://nips.cc/Conferences/2018/Videos OR https://videoken.com/embed

Amazing job on the work done so far.

Finally @kmario23 NYU has a new course on Responsible Data Science. Although there are no lectures available. The material itself is a huge resource for Ethical DL. since there are no other courses i implore you to do so xD. the link is https://dataresponsibly.github.io/courses/spring19/

Course Name: ESE 514: Graph Neural Networks, Fall 2021.
Instructor: Professor Alejandro Ribeiro, University of Pennsylvania.
Course WebPage: https://gnn.seas.upenn.edu/
Lecture Videos: https://www.youtube.com/channel/UC_YPrqpiEqkeGOG1TCt0giQ/playlists
Year: Fall 2021

We have amazing courses on Deep Learning and Digital Image Processing (focusing on the modern methods) at Technion, both given by Alex Bronstein.

Deep learning
YouTube playlist: https://www.youtube.com/watch?v=IclXQNHkYgI&list=PLM0a6Z788YAZuqg2Ip-_dPLzEd33lZvP2
Course website: https://vistalab-technion.github.io/cs236605/lectures/

Digital Image Processing
YouTube playlist: https://www.youtube.com/watch?v=d0Z4zRhK_Uo&list=PLM0a6Z788YAZOxUyWda9y3N_i2upIj1Ep
Course website: https://vistalab-technion.github.io/cs236860/lectures/

CSEP 517:

Youtube: https://www.youtube.com/playlist?list=PLU40WL8Ol94Ih1qEwkJr57vDRTtoZbwCI
Slides: https://courses.cs.washington.edu/courses/csep517/17sp/

CS769 Optimization in Machine Learning 2022

Course Name: STAT 37710 / CMSC 35400: Machine Learning, Spring 2020.
Instructor: Rebecca Willett, Yuxin Chen, University of Chicago.
Course WebPage: https://voices.uchicago.edu/willett/teaching/stats37710-cmsc35400-s20/
Lecture Videos: https://voices.uchicago.edu/willett/teaching/stats37710-cmsc35400-s20/
Year: Spring 2020

Hi,

there is a recently started course from UC Berkeley on Deep Unsupervised learning:
https://sites.google.com/view/berkeley-cs294-158-sp19/home

First lecture recording on youtube:
https://www.youtube.com/watch?v=zNmvH6OXDpk&feature=youtu.be

Machine Learning for Computer Vision by Fred Hamprecht of Uni Heidelberg
https://www.youtube.com/playlist?list=PLuRaSnb3n4kSQFyt8VBldsQ9pO9Xtu8rY

Current link of "MIT Deep Learning" is not working.
Link of that course is : https://www.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

Hi,
I think this is the most robust portal for our field I have ever seen, kudos.
How hard for you will it be to add either or both of the following features:
thumbs up and down
button per course with comments on the course

The list is so long that it is daunting, in such cases knowing others' responses would really help to choose.

For general Machine Learning:

http://www.cs.cornell.edu/courses/cs4780/2018fa/

https://www.youtube.com/playlist?list=PLl8OlHZGYOQ7bkVbuRthEsaLr7bONzbXS

1)Introduction to Deep Learning (I2DL) (IN2346)
https://www.youtube.com/playlist?list=PLQ8Y4kIIbzy_OaXv86lfbQwPHSomk2o2e
https://dvl.in.tum.de/teaching/i2dl-ss20/
2)Stat453: Introduction to Deep Learning and Generative Models (Spring 2020)
https://www.youtube.com/playlist?list=PLTKMiZHVd_2JkR6QtQEnml7swCnFBtq4P
http://pages.stat.wisc.edu/~sraschka/teaching/stat453-ss2020/
3)Deep Learning Course (2020)
https://www.youtube.com/playlist?list=PLmx4utxjUQD70k_NzeiSIXf30m54T_e1h
https://www.youtube.com/channel/UCUm7yUmVJyAbYh_0ppJ4H-g/videos
https://cedar.buffalo.edu/~srihari/CSE676/

http://www.cs.cmu.edu/~tom/10701_sp11/