In the paper A survey on bias and fairness in machine learning.- the authors outline 23 types of bias in data for machinelearning. The source is good – so below is an actual representation because I found it useful as it is

full paper link below

 

1) Historical Bias. Historical bias is the already…

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Summary:  Bias in modeling has long been a public concern that is now amplified and focused on the disparate treatment models may cause for African Americans.  Defining and correcting the bias presents difficult issues for data scientists that need to be carefully thought through before reaching conclusions.

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Profit analysis is an integral part of analysis drills, which are conducted at regular frequency. Both finance and marketing departments are equally engaged in this activity — though both have a different approach to it. Variance…

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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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Today I uploaded to github the first version of my book “QC Paulinesia” about Quantum Computing. The title is a play on the surname of the famous quantum scientist Wolfgang Pauli and the word "Polynesia". The book is based on a paper with the same name that I wrote in 2004. 

Here is  its github repo. Here is the pdf for the book. Let me quote the current…

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Background

Anomaly detection for IoT is one of the archetypal applications for IoT.

Anomaly detection techniques are also used outside of IoT.

In my teaching at the #universityofoxford - we use anomaly detection as a use case because it brings together many of…

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Yahoo Finance (below) is a website that gives us a good deal of information about the financial market, including information about stock trading.

To get the numbers for a specific stock, all you have to do is to search for its Yahoo code (ex: VALE - see figure below). This is not necessarily the company’s…

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The Problem

Millions of people are forced to leave their current area of residence or community due to resource shortage and natural disasters such as droughts, floods. Our project partner, UNHCR, provides assistance and protection for those who are forcibly displaced inside Somalia.

The goal of this project was to create a solution that quantifies…

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Generative Adversarial Networks (GANs) software is software for producing forgeries and imitations of data (aka synthetic data, fake data). Human beings have been making fakes, with good or evil intent, of almost everything they possibly can, since the beginning of the human race. Thus, perhaps not too surprisingly, GAN software has been widely used since it was first proposed in this amazingly recent 2014 paper. To gauge how widely GAN software has been used so far, see, for…

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© 2020 by Radna Intellectual Ventures, LLC.

In Sweden, there's something called the Allemansrätten, which literally translates…

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Given the scale of its impact and the kind of alteration that it brought into our lives, COVID19 is one of the most unprecedented crises of our times. Although it is not the only pandemic that humanity has been through, COVID19 is occurring in the time of the fourth industrial revolution where everyone and everything is one click way, and where the excess of data and computing has allowed machines to be more intelligent than ever. In the age of deep tech and data, data science is definitely…

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Recently Springer made some good books on maths free to download.

Competitive programming strategies are useful for many data science interviews and they help to improve your maths foundations.  There are not many books on this subject (although there are many good websites and YouTube resources).

So, I hope you find this book…

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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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Background

As part of my PhD work, I recently had to analyze any dataset(s) of my interest and present findings.  I ended up conducting a study on US County-wise Covid-19 data.  I wanted to share my key findings through this blog.

Study Question

The primary question I wanted to address through data analysis was “Do counties’ socioeconomic factors such as population size, poverty rate, unemployment rate, education percent and…

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Data Science and Data Analytics are two most common terminologies in today’s data driven world. How a business uses big data to make key business decisions is critical to the future success of the firm. Data is collected into raw form and processed according to the requirement of a company and then this data is utilized for the decision making purpose. This process helps the businesses to grow & expand their operations in the market. Data or information is typically in raw format. The… Continue

If you've spent any time with modeling data, you'll know that there are many pitfalls to be had when it comes to data presentation (I addressed some common pitfalls in Misleading Graphs Part 1). Misleading graphs can be the result of incorrect data collection, ignorance of the basic "rules" of data presentation (like labeling axes), or even deliberate attempts to mislead. A fourth…

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Data monetization is a hot topic these days.  Executives at both startups and large companies are being asked to capitalize on the value of their data assets and drive bottom line results.  According to McKinsey, in their paper "Fueling growth through Data Monetization", companies that invest in data monetization are outperformers in their category -- which is not surprising, given that application of data is highly…

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