NLP, Statistics, Probability: adding links to various sections across…

… the repo
jd-13 · Oct 23, 2019 · 914f8c4 · 914f8c4
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diff --git a/README-details.md b/README-details.md
@@ -403,6 +403,8 @@ See [Visualisation](README-details.md#visualisation-1)
   - [Probability Learning II: How Bayes’ Theorem is applied in Machine Learning](https://towardsdatascience.com/probability-learning-ii-how-bayes-theorem-is-applied-in-machine-learning-bd747a960962)
   - [Learning & Reasoning in Artificial Intelligence](https://www.youtube.com/watch?v=K_GOHepjY2o) by [Thomas Lukasiewicz](http://www.cs.ox.ac.uk/thomas.lukasiewicz/)
   - Abductive Learning: Towards Bridging Machine Learning and Logical Reasoning: [Slides](http://daiwz.net/org/slides/ABL-meetup.html) | [Video](https://www.youtube.com/watch?v=ETHrFxiFIUM) | [GitHub](https://github.com/AbductiveLearning/ABL-HED)
+  - [Coursera Course: Probability and distribution](
+https://media.licdn.com/dms/document/C511FAQGFKgIKuW_EEA/feedshare-document-pdf-analyzed/0?e=1571785200&v=beta&t=XyEEqUgi3y4L1hiZ7CxlxbAXyZmM_zcCCdn-Lr04ns8)
   - [Statistics by Chris Albon](https://chrisalbon.com/#statistics) - covering Frequentist topics
   - [See Data > Statistics section more related links](./data/README.md#statistics)
 
@@ -553,6 +555,7 @@ data visualisation. Magic from spreadsheets. Next-level storytelling. Embed on y
   - [Android App with cheatsheets](https://play.google.com/store/apps/details?id=com.youredufriends.datasciencehub)
   - [Algorithms related cheatsheets - Big-O cheatsheet](http://bigocheatsheet.com/)
   - [ML Cheatsheet by Nabih Ibrahim Bawazir](https://media.licdn.com/dms/document/C511FAQGFXvKuRmt5Rg/feedshare-document-pdf-analyzed/0?e=1569596400&v=beta&t=n4ZRWnYpc1KOTo8lZ2sKmOI7rRChPkApOQEQBBDhaXg)
+  - [Statistics cheatsheet](https://media.licdn.com/dms/document/C511FAQF31AWGmSTzMQ/feedshare-document-pdf-analyzed/0?e=1571943600&v=beta&t=9HwhZIlxIBW4zT7LLHyiJPA5djyKcjo4rFjiausHRn8)
 
 ### Misc
   - [Enterprise Data Analytics](https://www.dsta.gov.sg/docs/default-source/dsta-about/dh13201801_enterprise-data-analytics.pdf)

diff --git a/data/README.md b/data/README.md
@@ -192,6 +192,7 @@ See [Data Generation](./data-generation.md#data-generation)
 - [Journal of Statistical Software - TidyData](https://www.jstatsoft.org/article/view/v059i10/)
 - Statistics courses at [Coursera](https://www.coursera.org/courses?query=statistics&) | [Udemy](https://www.udemy.com/courses/search/?src=ukw&q=statistics) | [Udacity](https://eu.udacity.com/courses/all) - search for `Statistics` | Harvard University: [Statistics 110](https://www.youtube.com/watch?v=KbB0FjPg0mw&list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo) | [more videos on their YouTube channel](https://www.youtube.com/user/Harvard/search?query=statistics) | [Stanford University](https://online.stanford.edu/courses?keywords=statistics)
 - [15 Statistical Hypothesis Tests in Python (Cheat Sheet)](https://machinelearningmastery.com/statistical-hypothesis-tests-in-python-cheat-sheet/?fbclid=IwAR102PXBzIdx8g8zejg9ssE7at8jrnyfAtiT95Rp8flo98p8qEFBho5HOG0)
+- [Statistics cheatsheet](https://media.licdn.com/dms/document/C511FAQF31AWGmSTzMQ/feedshare-document-pdf-analyzed/0?e=1571943600&v=beta&t=9HwhZIlxIBW4zT7LLHyiJPA5djyKcjo4rFjiausHRn8)
 - [Statistics by Chris Albon](https://chrisalbon.com/#statistics) - covering Frequentist topics
 - For more, see [Mathematics, Statistics, Probability & Probabilistic programming](../README-details.md#mathematics-statistics-probability--probabilistic-programming)
 
@@ -225,6 +226,9 @@ See under [Cheatsheets](../README-details.md#cheatsheets)
 - [Data courses on Udacity](https://eu.udacity.com/courses/school-of-data-science)
 - [Latest Machine learning, visualization, data mining techniques. Online Masters in Data Analytic from Penn State](https://twitter.com/analyticbridge/status/1102667686302179336)
 - [Data Science Handbook](https://github.com/RishiSankineni/Data-Science-Swag/blob/master/The%20Data%20Science%20Handbook.pdf)
+- [Coursera Course: Probability and distribution](
+https://media.licdn.com/dms/document/C511FAQGFKgIKuW_EEA/feedshare-document-pdf-analyzed/0?e=1571785200&v=beta&t=XyEEqUgi3y4L1hiZ7CxlxbAXyZmM_zcCCdn-Lr04ns8)
+
 
 ## Best practices / rules / an unordered list of high level or low level guidelines
 - [12 Best Practices for Modern Data Ingestion](https://go.streamsets.com/dzone-wp-12-best-practices-modern-data-ingestion)

diff --git a/natural-language-processing/README.md b/natural-language-processing/README.md
@@ -97,8 +97,11 @@ NLP Java: [![NLP Java](https://img.shields.io/docker/pulls/neomatrix369/nlp-java
 - [Code resources for Central London Data Science Project Nights meetup on word vectors](https://github.com/central-ldn-data-sci/nlp-using-word-vectors)
 
 ## Presentations
+
 - [Natural Language Procoessing presentation by Ovidiu S.](../presentations/nlp/)
 - [Better NLP - presentations](../examples/better-nlp/presentations)
+- Training Multi-Billion Parameter Language Models with Megatron Webinar: [Slides](https://ssl.lvl3.on24.com/event/20/93/08/9/rt/1/documents/resourceList1571091756296/megatronwebinar17oct20191571091755100.pdf) | 
+[NVIDIA/Megatron-LM github](https://github.com/nvidia/megatron-lm) | [Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism](https://arxiv.org/abs/1909.08053) | [Subscribe to the Higher Education and Research Newsletter (Nvidia)](https://www.nvidia.com/en-us/industries/higher-education-research/#subscribe-me-solutions&ncid=em-webi-23619#cid=ix01_em-webi_en-us)
 
 ## Notebooks