Difference between revisions of "Reviews"
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*[https://github.com/mukeshmithrakumar/Book_List Python, Machine Learning, Deep Learning and Data Science Books] | *[https://github.com/mukeshmithrakumar/Book_List Python, Machine Learning, Deep Learning and Data Science Books] | ||
| − | = | + | =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] | ||
*[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] | *[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] | ||
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Revision as of 02:37, 30 December 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)
- AlgebraNets by Jordan Hoffmann et al., 2020
Statistics
- Overview of data distributions
- The control of the false discovery rate in multiple testing under dependency by Yoav Benjamini and Daniel Yekutieli, 2001
- Conjugate Priors for Generalized Linear Models by Ming-Hui Chen and Joseph G. Ibrahim, 2003
Programming
- [Papers with code]
- Over 200 of the Best Machine Learning, NLP, and Python Tutorials by Robbie Allen, 2018
Technical communications
- English Communication for Scientists by Nature Education, 2014
Writing a scientific article: A step-by-step guide for beginnersby F.Ecarnot et al., 2015 in European Geriatric Medicine- 11 steps to structuring a science paper editors will take seriously by By Angel Borja, 2014 in Elsevier connections
- How to Write a GoodScientific Paper by Chris A. Mack, 2018 in SPIE.org
Unsorted
News, sensationalism
- Deep learning: sate of the art by Lex Fridman, MIT, 2020
- 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