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Featured Blog Posts (1,486)

Free Book: Applied Stochastic Processes

Full title: Applied Stochastic Processes, Chaos Modeling, and Probabilistic Properties of Numeration Systems. Published June 2, 2018. Author: Vincent Granville, PhD. (104 pages, 16 chapters.)

This book is intended for professionals in data science, computer science, operations research, statistics, machine learning, big data, and mathematics. In 100 pages, it covers many new topics, offering a fresh perspective on the subject. It is accessible to…

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Added by Vincent Granville on September 8, 2018 at 11:16am — No Comments

Graph-based intelligence analysis

For decades, the intelligence community has been collecting and analyzing information to produce timely and actionable insights for intelligence consumers. But as the amount of information collected increases, analysts are facing new challenges in terms of data processing and analysis. In this article, we explore the possibilities that graph technology is offering for intelligence analysis.

Intelligence collection and analysis in the age of…

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Added by Elise Devaux on August 13, 2018 at 5:30am — 1 Comment

Invitation to Join Data Science Central

Join the largest community of machine learning (ML), deep learning, AI, data science, business analytics, BI, operations research, mathematical and statistical professionals: Sign up here. If instead, you are only interested in receiving our newsletter, you can subscribe here. There is no…

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Added by Vincent Granville on September 8, 2018 at 11:14am — No Comments

Type I and Type II Errors in One Picture

This picture speaks more than words. It explains the concept or false positive and false negative, that is, what is referred to by statisticians as Type I and Type II errors.

Other great pictures summarizing data science and statistical concepts, can be found…

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Added by Vincent Granville on August 10, 2017 at 5:17pm — No Comments

Linear Models Don’t have to Fit Exactly for P-Values To Be Accurate, Right, and Useful

There is no need to get confused with multiple linear regression, generalized linear model or general linear methods. The general linear model or multivariate regression model is a statistical linear model and is written as Y = XB + U.





Usually, a linear model includes a number of different statistical models such as ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary linear regression, t-test and F-test. The GLM is a generalization of multiple…

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Added by Chirag Shivalker on November 2, 2017 at 11:30pm — 1 Comment

High Precision Computing in Python or R

Here we discuss an application of HPC (not high performance computing, instead high precision computing, which is a special case of HPC)  applied to dynamical systems such as  the logistic map in chaos theory. defined as X(k) = 4 X(k) (1 - X(k-1)). 

For all these systems, the loss of precision propagates exponentially, to the point that after 50 iterations, all generated values are completely wrong. Tons of articles have been written on this subject - none of them acknowledging the…

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Added by Vincent Granville on November 13, 2017 at 7:00pm — No Comments

Supervised learning in disguise: the truth about unsupervised learning

One of the first lessons you’ll receive in machine learning is that there are two broad categories: supervised and unsupervised learning. Supervised learning is usually explained as the one to which you provide the correct answers, training data, and the machine learns the patterns to apply to new data. Unsupervised learning is (apparently) where the machine figures out the correct answer on its own.

Supposedly, unsupervised learning can discover something new that has not been found…

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Added by Danko Nikolic on February 14, 2018 at 1:00pm — No Comments

Machine Learning with Signal Processing Techniques

Stochastic Signal Analysis is a field of science concerned with the processing, modification and analysis of (stochastic) signals.

Anyone with a background in Physics or Engineering knows to some degree about signal analysis techniques, what these technique are and how they can be used to analyze, model and classify signals.

Data Scientists coming from a different fields, like Computer Science or Statistics, might not be aware of the analytical power these techniques bring with…

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Added by ahmet taspinar on April 29, 2018 at 9:00am — No Comments

20 Questions to Ask Prior to Starting Data Analysis

It is crucial to ask the right questions and/or understand the problem, prior to beginning data analysis. Below is a list of 20 questions you need to ask before delving into analysis:

  1. Who is the…
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Added by Cynthia Clare on May 23, 2018 at 8:30pm — No Comments

Curious Mathematical Problem

Let us consider the following equation:

Prove that

  • x = log(Pi) = 1.14472988584... is a very good approximation of a solution, up to 10 digits.
  • Using high…
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Added by Vincent Granville on August 30, 2018 at 11:00pm — 1 Comment

Top 10 PHP Frameworks for Website Design and Development

PHP, known as the most popular server-side scripting language in the world, has evolved a lot since the first inline code snippets appeared in static HTML files.

These days developers need to build complex websites and web apps, and above a certain complexity level it can take too much time and hassle to always start from scratch, hence came the need for a more structured natural way of development. PHP frameworks provide developers with an adequate solution for that.

Choosing…

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Added by Rajveer Singh Rathore on July 30, 2018 at 4:30am — No Comments

Mathematical Olympiads for Undergrad Students

Mathematical Olympiads are popular among high school students. However, there is nothing similar for college students, except maybe IMC. Even IMC is not popular. It focuses mostly on the same kind of problems as high school Olympiads, and you can not participate if you are over 23 years old. In addition, it is organized by country, as opposed to globally, thus favoring countries with a large population. Topics such as…

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Added by Vincent Granville on May 25, 2018 at 9:00am — No Comments

The Role of Predictive Analytics in Medical Diagnosis

Predictive analytics uses current and historical data in order to determine the probability of a particular outcome. This is a particularly powerful approach when it is applied to medical diagnosis. In an effort to reduce misdiagnosis, historical data of former patient’s symptoms may be applied to the assessment of a new patient.

While doctors are the ultimate experts and decision-makers, using predictive analytics as a means of establishing precedent for…

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Added by Goli Tajadod on May 22, 2018 at 2:30am — No Comments

I Analyzed 10 MM digits of SQRT(2) - Look at My Findings

This article is intended for practitioners who might not necessarily be statisticians or statistically-savvy. The mathematical level is kept as simple as possible, yet I present an original, simple approach to test for randomness, with an interesting application to illustrate the methodology. This material is not something usually discussed in textbooks or classrooms (even for statistical students), offering a fresh perspective, and out-of-the-box tools that are useful in many contexts, as…

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Added by Vincent Granville on March 31, 2018 at 10:30pm — 2 Comments

What is an Analytics Translator and Why is the Role Important to Your Organization?

Today, enterprises recognize the critical value of advanced analytics within the organization and they are implementing data democratization initiatives. As these initiatives evolve, new roles emerge in the organization. The newest of these analysis-related roles is the 'analytics translator'. As the enterprise considers the relevance of this new role within the business, it is important to understand the responsibilities of an Analytics…

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Added by Kartik Patel on February 23, 2018 at 2:30am — No Comments

What is Clickless Analysis? Can it Simplify Adoption of Augmented Analytics? (Part 1 of 3 articles)

The concept of Clickless Analytics is one that will be happily embraced by business users and by the business enterprise. The reason is simple! Clickless Analytics allows users to find and analyze information without specialized skills, by using natural language.

In this, the first of a three-part series we discuss Clickless Analytics and how it can simplify user adoption of augmented analytics.

What is Clickless Analytics?

Clickless Analytics…

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Added by Kartik Patel on January 25, 2018 at 5:30am — No Comments

Easy Dashboards for Everyone Using Google Data Studio

No matter the job, most professionals do some level of analysis on their computer.  There are always some data sets that live outside the walls.  Or, some analyses that we know could be performed better in a not-easily-sharable tool such as excel, R, python, SPSS, SAS and so on.

So how do you share your personal analysis with others?  Often times people export…

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Added by Laura Ellis on January 11, 2018 at 4:30pm — No Comments

Beautiful Number Theory Problem and Sandbox for Data Scientists

The Waring conjecture - actually a problem associated with a number of conjectures, many now being solved - is one of the most fascinating mathematical problems. This article covers new aspects of this problem, with a generalization and new conjectures, some with a tentative solution, and a new framework to tackle the problem. Yet it is written in simple English and accessible to the layman.

I also review a number of famous related mathematical conjectures, including one with a $1…

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Added by Vincent Granville on January 10, 2018 at 6:00pm — No Comments

6 Predictions about Data Science, Machine Learning, and AI for 2018

Summary:  Here are our 6 predictions for data science, machine learning, and AI for 2018.  Some are fast track and potentially disruptive, some take the hype off over blown claims and set realistic expectations for the coming year.

It’s that time of year again when we do a look back in order to offer a look forward.  What trends will speed up, what things will actually happen, and what things won’t in the coming year for data science, machine…

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Added by Vincent Granville on December 14, 2017 at 3:00pm — No Comments

Information Retrieval Document Search Engine in R

Introduction:

In this post, we learn about building a basic search engine or document retrieval system using Vector space model. This use case is widely used in information retrieval systems. Given a set of documents and search term(s)/query we need to retrieve relevant documents that are similar to the search query. 

Problem statement:

The problem statement explained above is represented as in below image. …

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Added by suresh kumar Gorakala on November 7, 2017 at 6:30am — No Comments

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