The methodology described here has broad applications, leading to new statistical tests, new type of ANOVA (analysis of variance), improved design of experiments, interesting fractional factorial designs, a better understanding of irrational numbers leading to cryptography, gaming and Fintech applications, and high quality random number generators (and when you really need them). It also features exact arithmetic / high performance computing and distributed algorithms to compute millions of…

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Data science uses many different probability distributions, but some are used more than others. This one picture shows an overview of five probability distributions data scientists will  find the most useful. See below the image for more information about the distributions.

Further Information:…

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We all know how horror movies work: there is someone evil in the neighborhood (like Michael Myers in “Halloween” or Freddy Krueger in “Nightmare on Elm Street” or Tom Cruise in “War of the Worlds”) and the soon-to-be-victim, we’ll say in this case, an unassuming CEO, wanders into a dark space (basement, closet, wood shed, attic) where the evil doer is waiting for them with a new agenda for the digital enterprise they can’t assimilate and they perish.

Slash! Cut! Gouge! Scream!…

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Machine Learning (ML) models are increasingly being used to augment human decision making process in domains such as finance, telecommunication, healthcare, and others. In most of the cases, users do not understand how these models make predictions. The lack of understanding makes it difficult for policy makers to justify their decisions. Most of the ML models are black boxes that do not explain on its own why it reached a specific recommendation or a decision. This forces the users to say…

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

Resources

• Filters in Computer Vision (with Images)
• Augmented Analytics Engine…

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Role of Augmented Analytics in Future !!  Insight generation is changing (and That’s a Good Thing)

 

Have you ever been in situation when you need quick insight generation but due to lack of resources and information you lost large amount of revenue? We live in data world, not only data but Big Data. Datasets are being generated in very large volume, variety and very high speed. Just forget about handling this type of data with your Traditional BI system. Due…

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#Coronavirus: The world sees a new disease which might become a global pandemic. It depends on how we act now.

But how should we act? Maybe #Datascience can help. But we data scientists have not enough data.

All I found is data about the spread per country/region (see my links in the group); I have not found cases, not found details. Let’s unite and make this an effort where we can…

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Filters are the key thing in Computer Vision(Processing image data). You would have probably used different kinds of filters like the blur filter, vintage filters, etc  in photo editing apps. Ever thought about how those filters work? . How do they give the…

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ELAINE Symbolic AI offers community tool to cure “TL;DR” Syndrome

 

The idea of applying Natural Language tool to advance human intelligence is not new. Examples can be found among popular search engines and chat-bots. These applications generally require Machine Learning ahead of lengthy preparations with “human in the loop” training datasets. These pre-requisites are cost intensive in terms of time, labor, infrastructure and skill.

 

A few years…

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Summary:  How to measure the degree and value of AI adoption among companies or even countries is hard.  Here’s a beginning proposal on how to get started.

 

We talk a great deal about whether there are enough data scientists to go around, whether our advancements in AI techniques are better than others, if…

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AI in healthcare is something that is revolutionizing the industry and medical treatment that we as the patients receive. But AI, in general, is making inroads into virtually every field and aspect of society. Healthcare AI companies like NVIDIA healthcare and Google DeepMind Health are breaking new ground, with innovations that are helping to save lives. Let's dive into the world of AI so that you can have a better understanding of what it is all about and where it is going.…

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Scikit-learn (also known as sklearn) is a widely used free software machine learning library for the Python programming language. It has been adopted by many companies and universities as it features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, and k-means. SKlearn is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Scikit-learn is largely written in Python…

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The days of waiting in a long queue to deposit some amount in your bank accounts are gone. The digitalization of the world has improved many concepts, including the ones from the banking and finance sectors. With the help of online banking, performing transactions has become quick…

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You are familiar with the term data lake. A data lake is a repository used to store unlimited volume of data. These days, most of the cloud service providers allow us to host scalable data lakes for storing data as it arrives. For using these data lakes, it is not required to structure the data and we can run different types of applications on it. Usually they are applications for big data analytics and machine learning. These applications need entire data to be present in one data lake and… Continue

This post is based on two insightful threads I read online (References below)

Based on these, I address the question of ‘The difference between Statistics and Data Science’. Traditionally, most people, including me, would say that ‘statistics came first and Data Science builds upon statistics’. This chain of thought is valid but as you see…

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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. To subscribe, follow this link.  …

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I live in Jacksonville, Florida, where the odds of a hurricane on any given day are "improbable". But does that mean I shouldn't stock up on hurricane supplies and have an emergency preparedness plan? Far from it. Hurricane Irma blew through my city in 2017, causing around $85 million in damage and the worst…

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“We are too busy building the solution to bother the customer to identify, validate, value and prioritize their requirements.” – Name not disclosed to protect the ignorant

I see this habit all the time with experienced people; the tendency to jump right into solution mode when dealing with customers. Many of these experienced “experts” have seen the “problem” so many times before, that they just “know” the right solution. Heck, sometimes these “experts” even cut off or…

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Here is our selection of featured articles and technical contributions posted since Monday.

Resources

• Which masters or PhD program should I choose for Data Science or AI?
• Popular Programming Languages:…

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This article was written by Prashant Gupta.

One of the major aspects of training your machine learning model is avoiding overfitting. The model will have a low accuracy if it is overfitting. This happens because your model is trying too hard to capture the noise in your training dataset. By noise…

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