github
/
cs-video-courses
mirror of https://github.com/Developer-Y/cs-video-courses.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

ML reorganization + more lectures

Browse Source 
Prof Roughgarden lectures
MOOCs
ML section reorganization
pull/1/head
Developer-Y 8 years ago committed by GitHub
parent 94b22da680
commit 21d7632446
1 changed files with 65 additions and 44 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 109
      README.md

109
README.md
Unescape View File

@ -56,6 +56,8 @@ Courses
- [CS 61B - Data Structures, UC Berkeley](https://people.eecs.berkeley.edu/~jrs/61b/) - [CS 61B - Data Structures, UC Berkeley](https://people.eecs.berkeley.edu/~jrs/61b/)
- [Fall 2006 - Prof. Jonathan Shewchuk](https://www.youtube.com/playlist?list=PL4BBB74C7D2A1049C) - [Fall 2006 - Prof. Jonathan Shewchuk](https://www.youtube.com/playlist?list=PL4BBB74C7D2A1049C)
- [Spring 16 - Josh Hug](http://datastructur.es/sp16/) - [Spring 16 - Josh Hug](http://datastructur.es/sp16/)
- [MOOC - Design and Analysis of Algorithms Part 1 - Prof Roughgarden - Coursera](https://www.youtube.com/playlist?list=PLLH73N9cB21W1TZ6zz1dLkyIm50HylGyg) ([Part 2](https://www.youtube.com/playlist?list=PLLH73N9cB21VPj3H2xwTTye5TC8-UniA2))
- [MOOC - Algorithms Part 1 - Prof Sedgewick](https://www.youtube.com/playlist?list=PLUX6FBiUa2g4YWs6HkkCpXL6ru02i7y3Q) ([Part 2](https://www.youtube.com/playlist?list=PLqD_OdMOd_6YixsHkd9f4sNdof4IhIima))
- [COP 3530 Data Structures and Algorithms, Prof Sahni, UFL](http://www.cise.ufl.edu/~sahni/cop3530/presentations.htm) ([Videos](http://www.cise.ufl.edu/academics/courses/preview/cop3530sahni/)) - [COP 3530 Data Structures and Algorithms, Prof Sahni, UFL](http://www.cise.ufl.edu/~sahni/cop3530/presentations.htm) ([Videos](http://www.cise.ufl.edu/academics/courses/preview/cop3530sahni/))
- [6.006 - Introduction to Algorithms, MIT OCW](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/) - [6.006 - Introduction to Algorithms, MIT OCW](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/)
- [CS 161 - Design and Analysis of Algorithms, Prof. Tim Roughgarden, Stanford University](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=IntroToAlgorithms) - [CS 161 - Design and Analysis of Algorithms, Prof. Tim Roughgarden, Stanford University](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=IntroToAlgorithms)
@ -76,6 +78,9 @@ Courses
- [ECS 222A - Graduate Level Algorithm Design and Analysis, UC Davis](http://web.cs.ucdavis.edu/~gusfield/cs222f07/videolist.html) - [ECS 222A - Graduate Level Algorithm Design and Analysis, UC Davis](http://web.cs.ucdavis.edu/~gusfield/cs222f07/videolist.html)
- [6.851 - Advanced Data Structures, MIT](http://courses.csail.mit.edu/6.851/spring14/lectures/) ([MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-851-advanced-data-structures-spring-2012/lecture-videos/)) - [6.851 - Advanced Data Structures, MIT](http://courses.csail.mit.edu/6.851/spring14/lectures/) ([MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-851-advanced-data-structures-spring-2012/lecture-videos/))
- [6.854 - Advanced Algorithms, MIT](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c) ([Prof. Karger lectures](https://www.youtube.com/channel/UCtv9PiQVUDzsT4yl7524DCg/videos)) - [6.854 - Advanced Algorithms, MIT](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c) ([Prof. Karger lectures](https://www.youtube.com/channel/UCtv9PiQVUDzsT4yl7524DCg/videos))
- [CS264 Beyond Worst-Case Analysis, Fall 2014 - Tim Roughgarden Lecture](http://theory.stanford.edu/~tim/f14/f14.html) ([Youtube](https://www.youtube.com/playlist?list=PLEGCF-WLh2RL8jsZpaf2tLHa5LotFEt5b))
- [CS364A Algorithmic Game Theory, Fall 2013 - Tim Roughgarden Lectures](https://www.youtube.com/playlist?list=PLEGCF-WLh2RJBqmxvZ0_ie-mleCFhi2N4)
- [CS364B Advanced Mechanism Design, Winter 2014 - Tim Roughgarden Lectures](https://www.youtube.com/playlist?list=PLEGCF-WLh2RI77PL4gwLld_OU9Zh3TCX9)
--------------------------------- ---------------------------------
@ -109,13 +114,16 @@ Courses
- [CS138 Distributed Computer Systems Spring 2016 - Brown University](http://cs.brown.edu/courses/csci1380/s16/syllabus.html) - [CS138 Distributed Computer Systems Spring 2016 - Brown University](http://cs.brown.edu/courses/csci1380/s16/syllabus.html)
- [CSEP 552: PMP Distributed Systems, Spring 2013 - University of Washington](http://courses.cs.washington.edu/courses/csep552/13sp/) ([Videos](http://courses.cs.washington.edu/courses/csep552/13sp/video/)) - [CSEP 552: PMP Distributed Systems, Spring 2013 - University of Washington](http://courses.cs.washington.edu/courses/csep552/13sp/) ([Videos](http://courses.cs.washington.edu/courses/csep552/13sp/video/))
- [CSE 490H: Scalable Systems: Design, Implementation and Use of Large Scale Clusters, Autumn 2008 - University of Washington](http://courses.cs.washington.edu/courses/cse490h/08au/lectures.htm) ([Videos](http://courses.cs.washington.edu/courses/cse490h/08au/video.htm)) - [CSE 490H: Scalable Systems: Design, Implementation and Use of Large Scale Clusters, Autumn 2008 - University of Washington](http://courses.cs.washington.edu/courses/cse490h/08au/lectures.htm) ([Videos](http://courses.cs.washington.edu/courses/cse490h/08au/video.htm))
- [MOOC - Cloud Computing Concepts - UIUC](https://www.youtube.com/playlist?list=PLFd87qVsaLhOkTLvfp6MC94iFa_1c9wrU)
------------------------------------------------------------ ------------------------------------------------------------
### Database Systems ### Database Systems
- [CS 5530 - Database Systems, Spring 2016, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCrercQNP9tTsjjPdgRVYvC7) - [CS 5530 - Database Systems, Spring 2016, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCrercQNP9tTsjjPdgRVYvC7)
- [MOOC - Database Stanford Dbclass](https://www.youtube.com/playlist?list=PL6hGtHedy2Z4EkgY76QOcueU8lAC4o6c3)
- [CSEP 544, Database Management Systems, Au 2015 - University of Washington](https://www.youtube.com/playlist?list=PLTPQEx-31JXjQYrUKvAjUTWgCYluHGs_L) - [CSEP 544, Database Management Systems, Au 2015 - University of Washington](https://www.youtube.com/playlist?list=PLTPQEx-31JXjQYrUKvAjUTWgCYluHGs_L)
- [Principles of Database Management, Bart Baesens](https://www.youtube.com/playlist?list=PLdQddgMBv5zEhlpqdiUcf9aTNEtmESgyl)
- [15-721 - Database Systems, CMU](http://15721.courses.cs.cmu.edu/spring2016/) ([Lectures - YouTube](https://www.youtube.com/playlist?list=PLSE8ODhjZXjbisIGOepfnlbfxeH7TW-8O)) - [15-721 - Database Systems, CMU](http://15721.courses.cs.cmu.edu/spring2016/) ([Lectures - YouTube](https://www.youtube.com/playlist?list=PLSE8ODhjZXjbisIGOepfnlbfxeH7TW-8O))
- [CS 186 - Database Systems, UC Berkeley, Spring 2015](https://sites.google.com/site/cs186spring2015/home/schedule-and-notes) ([Lectures- YouTube](https://www.youtube.com/playlist?list=PL-XXv-cvA_iBVK2QzAV-R7NMA1ZkaiR2y)) - [CS 186 - Database Systems, UC Berkeley, Spring 2015](https://sites.google.com/site/cs186spring2015/home/schedule-and-notes) ([Lectures- YouTube](https://www.youtube.com/playlist?list=PL-XXv-cvA_iBVK2QzAV-R7NMA1ZkaiR2y))
- [CS 6530 - Graduate-level Database Systems, Fall 2016, University of Utah](https://www.cs.utah.edu/~lifeifei/cs6530/) ([Lectures - YouTube](https://www.youtube.com/playlist?list=PLbuogVdPnkCqwHUcieMrytP453Ep0y6eI)) - [CS 6530 - Graduate-level Database Systems, Fall 2016, University of Utah](https://www.cs.utah.edu/~lifeifei/cs6530/) ([Lectures - YouTube](https://www.youtube.com/playlist?list=PLbuogVdPnkCqwHUcieMrytP453Ep0y6eI))
@ -143,49 +151,60 @@ Courses
-------------- --------------
### Machine Learning ### Machine Learning
- [StatLearning - Intro to Statistical Learning, Stanford University](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) - **Machine Learning**
- [CS 156 - Learning from Data, Caltech](https://work.caltech.edu/lectures.html) - [Stanford: Machine Learning](https://www.youtube.com/playlist?list=PLJ1-ciQ35nuiyL1PX6O4NdF5CjjaDdnVC)
- [10-601 - Machine Learning, Carnegie Mellon University](http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml) - [StatLearning - Intro to Statistical Learning, Stanford University](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about)
- [Microsoft Research - Machine Learning Course](https://www.youtube.com/playlist?list=PL34iyE0uXtxo7vPXGFkmm6KbgZQwjf9Kf) - [CS 156 - Learning from Data, Caltech](https://work.caltech.edu/lectures.html)
- [CS 446 - Machine Learning, Fall 2016, UIUC](http://l2r.cs.illinois.edu/~danr/Teaching/CS446-16/schedule.html)([Fall 2015 Lectures](https://www.youtube.com/playlist?list=PLQcasX5-oG91n10wPxeRh-45-8HATwc8W)) - [10-601 - Machine Learning, Carnegie Mellon University](http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml)
- [undergraduate machine learning at UBC 2012, Nando de Freitas](https://www.youtube.com/playlist?list=PLE6Wd9FR--Ecf_5nCbnSQMHqORpiChfJf) - [Microsoft Research - Machine Learning Course](https://www.youtube.com/playlist?list=PL34iyE0uXtxo7vPXGFkmm6KbgZQwjf9Kf)
- [CS 229 - Machine Learning - Stanford University](https://www.youtube.com/playlist?list=PLA89DCFA6ADACE599) - [CS 446 - Machine Learning, Fall 2016, UIUC](http://l2r.cs.illinois.edu/~danr/Teaching/CS446-16/schedule.html)([Fall 2015 Lectures](https://www.youtube.com/playlist?list=PLQcasX5-oG91n10wPxeRh-45-8HATwc8W))
- [CS 189/289A Introduction to Machine Learning, Prof Jonathan Shewchuk - UCBerkeley](https://people.eecs.berkeley.edu/~jrs/189/) - [undergraduate machine learning at UBC 2012, Nando de Freitas](https://www.youtube.com/playlist?list=PLE6Wd9FR--Ecf_5nCbnSQMHqORpiChfJf)
- [CS 5140/6140 - Data Mining, Spring 2016, University of Utah](https://www.cs.utah.edu/~jeffp/teaching/cs5140.html) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLbuogVdPnkCpXfb43Wvc7s5fXWzedwTPB)) - [CS 229 - Machine Learning - Stanford University](https://www.youtube.com/playlist?list=PLA89DCFA6ADACE599)
- [CS 5350/6350 - Machine Learning, Fall 2016, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCozRSsdueVwX7CF9N4QWL0B) - [CS 189/289A Introduction to Machine Learning, Prof Jonathan Shewchuk - UCBerkeley](https://people.eecs.berkeley.edu/~jrs/189/)
- [ECE 5984 Introduction to Machine Learning, Spring 2015 - Virginia Tech](https://filebox.ece.vt.edu/~s15ece5984/) - [CS 5350/6350 - Machine Learning, Fall 2016, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCozRSsdueVwX7CF9N4QWL0B)
- [CS 6190 - Probabilistic Modeling, Spring 2016, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCpvxdF-Gy3gwaBObx7AnQut) - [ECE 5984 Introduction to Machine Learning, Spring 2015 - Virginia Tech](https://filebox.ece.vt.edu/~s15ece5984/)
- [CS 6955 - Clustering, Spring 2015, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCpRvi-qSMCdOwyn4UYoPxTI) - [CSEP 546, Machine Learning, Sp 2016 - University of Washington](https://courses.cs.washington.edu/courses/csep546/16sp/) ([Lectures - YouTube](https://www.youtube.com/playlist?list=PLTPQEx-31JXgtDaC6-3HxWcp7fq4N8YGr))
- [DS-GA 1008 - Deep Learning, New York University](http://cilvr.cs.nyu.edu/doku.php?id=deeplearning2015:schedule) - [STA 4273H (Winter 2015): Large Scale Machine Learning](http://www.cs.toronto.edu/~rsalakhu/STA4273_2015/lectures.html)
- [Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information](http://www.ischool.berkeley.edu/newsandevents/audiovideo/webcast/21963) - **Data Mining**
- [Machine Learning 2013 - Nando de Freitas, UBC](https://www.youtube.com/playlist?list=PLE6Wd9FR--EdyJ5lbFl8UuGjecvVw66F6) - [CS 5140/6140 - Data Mining, Spring 2016, University of Utah](https://www.cs.utah.edu/~jeffp/teaching/cs5140.html) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLbuogVdPnkCpXfb43Wvc7s5fXWzedwTPB))
- [Machine Learning: 2014-2015, University of Oxford](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) - [Statistical Aspects of Data Mining (Stats 202) - Google](https://www.youtube.com/playlist?list=PLFE776F2C513A744E)
- [Deep learning at Oxford 2015 - Nando de Freitas](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu) - [MOOC - Text Mining and Analytics by ChengXiang Zhai](https://www.youtube.com/playlist?list=PLLssT5z_DsK8Xwnh_0bjN4KNT81bekvtt)
- [10-701 Machine Learning - Tom Mitchell, Spring 2011, Carnegie Mellon University](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) ([Fall 2014](https://www.youtube.com/playlist?list=PL7y-1rk2cCsDZCVz2xS7LrExqidHpJM3B)) - [MOOC - Data Mining with Weka](https://www.youtube.com/playlist?list=PLm4W7_iX_v4NqPUjceOGd-OKNVO4c_cPD)
- [10-702/36-702 - Statistical Machine Learning - Larry Wasserman, Spring 2016, CMU](http://www.stat.cmu.edu/~larry/=sml/) ([Spring 2015](https://www.youtube.com/playlist?list=PLjbUi5mgii6BWEUZf7He6nowWvGne_Y8r)) - [CS 290 DataMining Lectures](https://www.youtube.com/playlist?list=PLB4CCA346A5741C4C)
- [10-708 - Probabilistic Graphical Models, Carnegie Mellon University](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html) - **Probabilistic Graphical Modeling**
- [10-725 Convex Optimization: Spring 2015 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt-S15/) - [CS 6190 - Probabilistic Modeling, Spring 2016, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCpvxdF-Gy3gwaBObx7AnQut)
- [10-801 Advanced Optimization and Randomized Algorithms](https://www.youtube.com/playlist?list=PLjTcdlvIS6cjdA8WVXNIk56X_SjICxt0d) - [10-708 - Probabilistic Graphical Models, Carnegie Mellon University](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [36-705 - Intermediate Statistics - Larry Wasserman, CMU](http://www.stat.cmu.edu/~larry/=stat705/) - [Probabilistic Graphical Models, Daphne Koller, Stanford University](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=ProbabilisticGraphicalModels)
- [CS 224d - Deep Learning for Natural Language Processing, Stanford University](http://cs224d.stanford.edu/syllabus.html) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLCJlDcMjVoEdtem5GaohTC1o9HTTFtK7_)) - **Deep Learning**
- [CS 224N - Natural Language Processing, Stanford University](https://www.youtube.com/playlist?list=PLgtM85Maly3n2Fp1gJVvqb0bTC39CPn1N) - [Deep learning at Oxford 2015 - Nando de Freitas](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu)
- [CS 229r - Algorithms for Big Data, Harvard University](http://people.seas.harvard.edu/~minilek/cs229r/fall15/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0v1kQTpqpuu5kEJo2i-iUyf)) - [DS-GA 1008 - Deep Learning, New York University](http://cilvr.cs.nyu.edu/doku.php?id=deeplearning2015:schedule)
- [CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University](https://www.youtube.com/playlist?list=PLLvH2FwAQhnpj1WEB-jHmPuUeQ8mX-XXG) - [Deep Learning, Stanford University](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=DeepLearning)
- [CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas](http://granite.ices.utexas.edu/coursewiki/index.php/Main_Page) - [Deep Learning - University of Waterloo](https://uwaterloo.ca/data-science/deep-learning)
- [Probabilistic Graphical Models, Daphne Koller, Stanford University](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=ProbabilisticGraphicalModels) - **Advanced Machine Learning**
- [Deep Learning, Stanford University](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=DeepLearning) - [Machine Learning 2013 - Nando de Freitas, UBC](https://www.youtube.com/playlist?list=PLE6Wd9FR--EdyJ5lbFl8UuGjecvVw66F6)
- [Statistical Learning- Classification - University of Waterloo](https://uwaterloo.ca/data-science/statistical-learning-classification) - [Machine Learning: 2014-2015, University of Oxford](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
- [Deep Learning - University of Waterloo](https://uwaterloo.ca/data-science/deep-learning) - [10-701 Machine Learning - Tom Mitchell, Spring 2011, Carnegie Mellon University](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) ([Fall 2014](https://www.youtube.com/playlist?list=PL7y-1rk2cCsDZCVz2xS7LrExqidHpJM3B))
- [9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT](https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O) - [10-702/36-702 - Statistical Machine Learning - Larry Wasserman, Spring 2016, CMU](http://www.stat.cmu.edu/~larry/=sml/) ([Spring 2015](https://www.youtube.com/playlist?list=PLjbUi5mgii6BWEUZf7He6nowWvGne_Y8r))
- [STA 4273H (Winter 2015): Large Scale Machine Learning](http://www.cs.toronto.edu/~rsalakhu/STA4273_2015/lectures.html) - [10-715 Advanced Introduction to Machine Learning - CMU](http://www.cs.cmu.edu/~bapoczos/Classes/ML10715_2015Fall/) ([YouTube](https://www.youtube.com/playlist?list=PL4DwY1suLMkcu-wytRDbvBNmx57CdQ2pJ))
- [CSEP 546, Machine Learning, Sp 2016 - University of Washington](https://courses.cs.washington.edu/courses/csep546/16sp/) ([Lectures - YouTube](https://www.youtube.com/playlist?list=PLTPQEx-31JXgtDaC6-3HxWcp7fq4N8YGr)) - **Natural Language Processing and Computer Vision**
- [Machine Learning for Computer Vision - TUM](https://www.youtube.com/playlist?list=PLTBdjV_4f-EIiongKlS9OKrBEp8QR47Wl) - [CS 224d - Deep Learning for Natural Language Processing, Stanford University](http://cs224d.stanford.edu/syllabus.html) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLCJlDcMjVoEdtem5GaohTC1o9HTTFtK7_))
- [Lecture: Variational Methods for Computer Vision (Prof. D. Cremers) TUM](https://www.youtube.com/playlist?list=PLTBdjV_4f-EJ7A2iIH5L5ztqqrWYjP2RI) - [CS 224N - Natural Language Processing, Stanford University](https://www.youtube.com/playlist?list=PLgtM85Maly3n2Fp1gJVvqb0bTC39CPn1N)
- [CAP 5415 - Computer Vision, University of Central Florida](http://crcv.ucf.edu/courses/CAP5415/Fall2014/index.php) - [MOOC - Natural Language Processing - Coursera, University of Michigan](https://www.youtube.com/playlist?list=PLLssT5z_DsK8BdawOVCCaTCO99Ya58ryR)
- [CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University](https://www.youtube.com/playlist?list=PLLvH2FwAQhnpj1WEB-jHmPuUeQ8mX-XXG)
- [Machine Learning for Computer Vision - TUM](https://www.youtube.com/playlist?list=PLTBdjV_4f-EIiongKlS9OKrBEp8QR47Wl)
- [Lecture: Variational Methods for Computer Vision (Prof. D. Cremers) TUM](https://www.youtube.com/playlist?list=PLTBdjV_4f-EJ7A2iIH5L5ztqqrWYjP2RI)
- [CAP 5415 - Computer Vision, University of Central Florida](http://crcv.ucf.edu/courses/CAP5415/Fall2014/index.php)
- **Misc Machine Learning Topics**
- [CS 6955 - Clustering, Spring 2015, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCpRvi-qSMCdOwyn4UYoPxTI)
- [Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information](http://www.ischool.berkeley.edu/newsandevents/audiovideo/webcast/21963)
- [10-725 Convex Optimization: Spring 2015 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt-S15/)
- [10-801 Advanced Optimization and Randomized Algorithms](https://www.youtube.com/playlist?list=PLjTcdlvIS6cjdA8WVXNIk56X_SjICxt0d)
- [CS 229r - Algorithms for Big Data, Harvard University](http://people.seas.harvard.edu/~minilek/cs229r/fall15/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0v1kQTpqpuu5kEJo2i-iUyf))
- [CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas](http://granite.ices.utexas.edu/coursewiki/index.php/Main_Page)
- [Statistical Learning- Classification - University of Waterloo](https://uwaterloo.ca/data-science/statistical-learning-classification)
- [9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT](https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O)
------------------------------ ------------------------------
### Concurrency ### Concurrency
@ -209,14 +228,16 @@ Courses
- [6.042J - Mathematics for Computer Science, Fall 2010, MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/video-lectures/) - [6.042J - Mathematics for Computer Science, Fall 2010, MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/video-lectures/)
- [6.042J - Mathematics for Computer Science, Spring 15, MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-spring-2015/index.htm) - [6.042J - Mathematics for Computer Science, Spring 15, MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-spring-2015/index.htm)
- [Computer Science 70, 001 - Fall 2012](https://www.youtube.com/playlist?list=PL1A2EBAC4283FE3EA) - [Computer Science 70, 001 - Fall 2012](https://www.youtube.com/playlist?list=PL1A2EBAC4283FE3EA)
- [Probabilistic Systems Analysis and Applied Probability](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013/) - [6.041 Probabilistic Systems Analysis and Applied Probability - MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013/)
- [10-600 Math Background for ML - CMU](https://www.youtube.com/playlist?list=PL7y-1rk2cCsA339crwXMWUaBRuLBvPBCg) - [10-600 Math Background for ML - CMU](https://www.youtube.com/playlist?list=PL7y-1rk2cCsA339crwXMWUaBRuLBvPBCg)
- [Linear Algebra Review - CMU](http://www.cs.cmu.edu/~zkolter/course/linalg/outline.html) - [Linear Algebra Review - CMU](http://www.cs.cmu.edu/~zkolter/course/linalg/outline.html)
- [STATS 250 - Introduction to Statistics and Data Analysis, UMichigan](https://www.youtube.com/playlist?list=PL432AB57AF9F43D4F)
- [131B - Introduction to Probability and Statistics, UCI](https://www.youtube.com/playlist?list=PLqOZ6FD_RQ7k-j-86QUC2_0nEu0QOP-Wy)
- [Statistics 110: Probability](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo) - [Statistics 110: Probability](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo)
- [18.06 - Linear Algebra, Prof. Gilbert Strang, MIT OCW](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/) - [18.06 - Linear Algebra, Prof. Gilbert Strang, MIT OCW](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/)
- [36-705 - Intermediate Statistics - Larry Wasserman, CMU](http://www.stat.cmu.edu/~larry/=stat705/)
- [STATS 250 - Introduction to Statistics and Data Analysis, UMichigan](https://www.youtube.com/playlist?list=PL432AB57AF9F43D4F)
- [131B - Introduction to Probability and Statistics, UCI](https://www.youtube.com/playlist?list=PLqOZ6FD_RQ7k-j-86QUC2_0nEu0QOP-Wy)
- [Multiple View Geometry - Lecture 1 (Prof. Daniel Cremers) TUM](https://www.youtube.com/playlist?list=PLTBdjV_4f-EJn6udZ34tht9EVIW7lbeo4) - [Multiple View Geometry - Lecture 1 (Prof. Daniel Cremers) TUM](https://www.youtube.com/playlist?list=PLTBdjV_4f-EJn6udZ34tht9EVIW7lbeo4)
- [The Probability and Statistics Full Course - YouTube](https://www.youtube.com/playlist?list=PLLssT5z_DsK_WYzNXVjT695FdxRxvlSF8)
------------------------- -------------------------

Write Preview
Loading…
Cancel
Save