Difference between revisions of "Reviews"
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*[https://www.encyclopediaofmath.org Encyclopedia of Mathematics wiki by Kluwer Academic Publishers, 2002] | *[https://www.encyclopediaofmath.org Encyclopedia of Mathematics wiki by Kluwer Academic Publishers, 2002] | ||
*[https://dasayan05.github.io/blog-tut/2020/05/05/probabilistic-programming.html?fbclid=IwAR1WBNV3HPQHw5QVJc9esfIgNII1jT8RxSRMnfFigpTjehwObSQL5SUH1HA Introduction to Probabilistic Programming by Ayan Das, 2020] | *[https://dasayan05.github.io/blog-tut/2020/05/05/probabilistic-programming.html?fbclid=IwAR1WBNV3HPQHw5QVJc9esfIgNII1jT8RxSRMnfFigpTjehwObSQL5SUH1HA Introduction to Probabilistic Programming by Ayan Das, 2020] | ||
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| + | =Mathematics for machine learning= | ||
| + | *[https://arxiv.org/abs/1911.00892v1 Boosting Vector Calculus with the Graphical Notation by Joon-Hwi Kim et al., 2019] | ||
=Functional data analysis= | =Functional data analysis= | ||
*[https://www.math3ma.com/ Math3ma by Thai-Danae Bradley, 2020] | *[https://www.math3ma.com/ Math3ma by Thai-Danae Bradley, 2020] | ||
| + | *[https://arxiv.org/abs/2004.05631 At the Interface of Algebra and Statistics by Tai-Danae Bradley, 2020] (category theory) | ||
=Statistics= | =Statistics= | ||
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*[https://towardsdatascience.com/when-bayes-ockham-and-shannon-come-together-to-define-machine-learning-96422729a1ad When Bayes, Ockham, and Shannon come together to define machine learning by Tirthajyoti Sarkar, 2018] | *[https://towardsdatascience.com/when-bayes-ockham-and-shannon-come-together-to-define-machine-learning-96422729a1ad When Bayes, Ockham, and Shannon come together to define machine learning by Tirthajyoti Sarkar, 2018] | ||
*[https://www.analyticsvidhya.com/blog/2017/12/introduction-to-recurrent-neural-networks/?fbclid=IwAR0s_QEvbVupVO-OAFwLOvWQPynUc70FCIxV-XEm4y0Md-0RWRLv18r8-Mc Introduction to Recurrent Neural Networks by Dishashree Gupta, 2017] | *[https://www.analyticsvidhya.com/blog/2017/12/introduction-to-recurrent-neural-networks/?fbclid=IwAR0s_QEvbVupVO-OAFwLOvWQPynUc70FCIxV-XEm4y0Md-0RWRLv18r8-Mc Introduction to Recurrent Neural Networks by Dishashree Gupta, 2017] | ||
| + | *[https://medium.com/@jehillparikh/bayes-by-back-prop-bbb-from-robust-neural-networks-to-unified-theory-of-brain-788fd83f0e38 Bayes by Backprop (BBB): Robust Neural Networks to Unified theory of Brain? by Jehill Parikh, 2019] | ||
| + | |||
| + | =News, sensationalism= | ||
| + | *[https://drive.google.com/file/d/10rZ4ldHUBoDu8bVoqGn-CEqGgX-w-oKm/view?fbclid=IwAR0FKijayJz4QO3IeC6_D7766TRMEwIDPlJp_JzaoSV5Bh7e7OxJ7Xukb2I Deep learning: sate of the art by Lex Fridman, MIT, 2020] | ||
Revision as of 04:10, 19 May 2020
Contents
Encyclopediae
- MathWorld Encyclopedia by wolfram
- Encyclopedia of Mathematics wiki by Kluwer Academic Publishers, 2002
- Introduction to Probabilistic Programming by Ayan Das, 2020
Mathematics for machine learning
Functional data analysis
- Math3ma by Thai-Danae Bradley, 2020
- At the Interface of Algebra and Statistics by Tai-Danae Bradley, 2020 (category theory)
Statistics
Programming
- [Papers with code]
- Over 200 of the Best Machine Learning, NLP, and Python Tutorials by Robbie Allen, 2018
Unsorted
Reviews for teenagers
- When Bayes, Ockham, and Shannon come together to define machine learning by Tirthajyoti Sarkar, 2018
- Introduction to Recurrent Neural Networks by Dishashree Gupta, 2017
- Bayes by Backprop (BBB): Robust Neural Networks to Unified theory of Brain? by Jehill Parikh, 2019