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    <title>Statistics, Econometrics and Machine Learning</title>
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    <description>Recent content on Statistics, Econometrics and Machine Learning</description>
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      <title>About</title>
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      <pubDate>Sat, 01 Aug 2020 00:00:00 +0000</pubDate>
      
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      <description>This a website on Statistics, Econometrics and Machine Learning. Still under construction</description>
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      <title>Useful Links</title>
      <link>/2020/08/01/my-first-post/</link>
      <pubDate>Sat, 01 Aug 2020 00:00:00 +0000</pubDate>
      
      <guid>/2020/08/01/my-first-post/</guid>
      <description>Courses Statistics http://www.stat.cmu.edu/~arinaldo/Teaching/36755/F16/
http://www.stat.ucla.edu/~arashamini/teaching/200c
https://www.cs.princeton.edu/courses/archive/fall11/cos597C/
http://www.biostat.jhsph.edu/bstcourse/bio771/
(https://stats385.github.io/
Bayesian Modelling http://mlg.eng.cam.ac.uk/zoubin/talks/lect1bayes.pdf
http://www.stat.cmu.edu/~larry/=sml/Bayes.pdf
Machine Learning http://cs229.stanford.edu/
https://www.coursera.org/specializations/machine-learning-algorithms-real-world
https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/
https://www.youtube.com/watch?v=BCiZc0n6COY&amp;amp;list=PLruBu5BI5n4aFpG32iMbdWoRVAA-Vcso6
https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006/
https://www.cs.cmu.edu/afs/cs/academic/class/15782-f06/slides/
https://mila.quebec/en/cours/
Deep Learning https://madewithml.com/
!https://www.fast.ai/
https://d2l.ai/
http://introtodeeplearning.com/
https://deeplearning.mit.edu/
https://fullstackdeeplearning.com/
https://www.youtube.com/deepmind
https://sijunhe.github.io/blog/2017/03/27/reading-notes-the-1986-backpropagation-paper/
https://blog.floydhub.com/
https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/
https://www.youtube.com/watch?v=0VH1Lim8gL8)
Courses http://www.cs.toronto.edu/~rgrosse/courses/csc421_2019/
https://www.cs.toronto.edu/~guerzhoy/321/
https://jimmylba.github.io/
https://www.lri.fr/~gcharpia/deeppractice/
https://web.cs.ucdavis.edu/~yjlee/teaching/ecs289g-winter2018/
https://drive.google.com/file/d/1pUUlnJswxF3JveKhcfoopAUTvNxAyHaI/view
https://sites.google.com/mila.quebec/ift6135/lectures
https://github.com/khipu-ai/practicals-2019
http://web.stanford.edu/class/cs224n/
https://smartech.gatech.edu/handle/1853/60926
https://sites.google.com/view/berkeley-cs294-158-sp20/home
https://www.math.ias.edu/wtd
Software https://github.com/mila-iqia/welcome_tutorials
https://web.stanford.edu/class/cs20si/
https://github.com/chiphuyen/stanford-tensorflow-tutorials
https://top10onlinecourses.com/best-pytorch-online-courses/
https://cs230.stanford.edu/blog/pytorch/
Reinforcement Learning https://www.coursera.org/specializations/reinforcement-learning
https://www.youtube.com/watch?v=FgzM3zpZ55o&amp;amp;amp;list=PLoROMvodv4rOSOPzutgyCTapiGlY2Nd8u
https://spinningup.openai.com/en/latest/
https://sites.google.com/view/rltheoryseminars/
https://www.youtube.com/watch?v=2pWv7GOvuf0&amp;amp;list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ
http://videolectures.net/DLRLsummerschool2018_sutton_introduction/
https://sites.google.com/view/deep-rl-bootcamp/lectures
https://link.springer.com/chapter/10.1007/978-3-540-68003-1_4
Causal Machine Learning https://crl.causalai.net/](https://crl.causalai.net/
http://bayes.cs.ucla.edu/BOOK-2K/viewgraphs.html
https://sites.google.com/site/faim18wscausalml/p
https://faculty.arts.ubc.ca/pschrimpf/628/machineLearningAndCausalInference.html
Summer Schools / Online Courses http://mlss.</description>
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