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Vincent Granville's Blog – October 2018 Archive (18)

New Book: Enterprise AI - An Applications Perspective

Now published. Enterprise AI: An applications perspective takes a use case driven approach to understand the deployment of AI in the Enterprise. Designed for strategists and developers, the book provides a practical and straightforward roadmap based on application use cases for AI in Enterprises. The authors (Ajit Jaokar and Cheuk Ting Ho) are data scientists and AI researchers who have deployed AI applications for Enterprise domains. The book is used as a reference for Ajit and Cheuk's new…

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Added by Vincent Granville on October 31, 2018 at 12:30pm — 2 Comments

25 Statistical Concepts Explained in Simple English - Part 2

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

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Added by Vincent Granville on October 30, 2018 at 10:00am — 1 Comment

Cool Problems in Probabilistic Number Theory and Set Theory

Here are a few off-the-beaten-path problems at the intersection of computer science (algorithms), probability, statistical science, set theory, and number theory. While they can easily be understood by beginners, finding a full solution to some of them is not easy, and some of the simple but deep questions below won't be answered for a long time, if ever, even by the best mathematicians living today. In some sense, this is the opposite of classroom exercises, as there is no sure path that…

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Added by Vincent Granville on October 29, 2018 at 6:00pm — 5 Comments

Weekly Digest, October 29

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.

Featured Resources and Technical Contributions 

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Added by Vincent Granville on October 28, 2018 at 9:00am — No Comments

One Trillion Random Digits

You will find here a few tables of random digits, used for simulation purposes and/or testing or integration in statistical, mathematical, and machine learning algorithms. These tables are particularly useful if you want to share your algorithms or simulations, and make them replicable. We also provide techniques to use in applications where secrecy is critical, such as cryptography, bitcoin or lotteries: in this case, you don't want to share your table of random numbers; to the contrary you…

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Added by Vincent Granville on October 27, 2018 at 9:00am — No Comments

Why do people with no experience want to become data scientists?

Below is my contrarian answer to one question recently posted on Quora.

It depends on what you mean by “no experience”. An NASA scientist who has processed petabytes of data and found great insights, for example discovered exoplanets, is de facto a data scientist and may have no interest in having his job title changed.

Then there is a bunch of people who call themselves “data science enthusiasts” and know nothing other than what they learned in a two-hour…

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Added by Vincent Granville on October 25, 2018 at 6:00pm — 1 Comment

Thursday News: Stats, Math, ML, Neural Nets, K-means, AI, Deep Learning, Python, Anomaly Detection

Here is our selection of featured articles and technical resources posted since Monday:

Resources

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Added by Vincent Granville on October 25, 2018 at 8:30am — No Comments

29 Statistical Concepts Explained in Simple English - Part 1

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

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Added by Vincent Granville on October 23, 2018 at 4:30pm — 4 Comments

Why is Becoming a Data Scientist so Difficult?

This question was recently posted on Quora. Below is my answer.

It depends what kind of data scientist you want to become. I think many university curricula include material that is advanced but that you don’t really need. Also, they offer not enough practical, professional coding and big data manipulation that would help you right away when starting a career. It also depends on your background: mine was math, stats, data analysis, and applied computer science, so the…

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Added by Vincent Granville on October 22, 2018 at 12:00pm — No Comments

Weekly Digest, October 22

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.

Announcement…

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Added by Vincent Granville on October 21, 2018 at 2:30am — No Comments

Thursday News: ML, Neural Nets (CNN), XGboost, Agile Analytics, Spatial Analytics

Here is our selection of featured resources, forum questions, and articles posted since Monday.

Resources

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Added by Vincent Granville on October 18, 2018 at 9:00am — No Comments

11 Great Articles about Stochastic Processes and Related Topics

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting,…

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Added by Vincent Granville on October 16, 2018 at 7:00pm — No Comments

Weekly Digest, October 15

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.

Announcement
  • Verizon—Solutions Engineers (Analysts) - Las Colinas, TX & Cary, NC



    Verizon is looking for Analysts who can use their technical and sales…
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Added by Vincent Granville on October 14, 2018 at 6:00am — No Comments

Thursday News: AI, Python, R, Excel, BI, Reinforcement Learning, NLP, 'No Code' Data Science

This is our selection of featured resources and articles posted since Monday.

Resources (Technical)

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Added by Vincent Granville on October 11, 2018 at 8:00am — No Comments

Free eBook: Enterprise AI - An Applications Perspective

By Ajit Jaokar and Cheuk Ting Ho.

Exclusively for Data Science Central members, with free access. You can download this book (PDF) here

Introduction

Enterprise AI: An applications perspective takes a use case driven approach to understanding the deployment of AI in the Enterprise. Designed for strategists and…

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Added by Vincent Granville on October 10, 2018 at 6:00am — 4 Comments

Weekly Digest, October 8

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.

Announcement

  • Big data is a big buzzword in the business world. But it’s a serious concept, referring to data sets so large and complex that traditional data-processing applications simply…
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Added by Vincent Granville on October 7, 2018 at 8:30am — No Comments

Ajit Jaokar Retrospective: AI, ML, IoT, Data Science Articles

Ajit's research is focused on Data Science for IoT. He teaches the same at Oxford University and UPM in Madrid (@forumoxford + @citysciences). Ajit is also launching a course / certification in Data Sciences for Industrial IoT. His personal research interests include Deep Learning algorithms for IoT/future city domains.

The selection below features…

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Added by Vincent Granville on October 4, 2018 at 9:00am — No Comments

Thursday News: AI, IoT, Datasets, Deep Learning, Python vs R

This is our selection of featured articles and resources posted since Monday:

Technical Resources

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Added by Vincent Granville on October 4, 2018 at 8:00am — No Comments

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