Featured Blog Posts – May 2018 Archive (84)

Few Machine Learning Problems (with Python implementation)

1. Back-propagation

This problem also appeared as an assignment problem in the coursera online course Mathematics for Machine Learning: Multivariate Calculus. The description of the problem is taken from the assignment itself.

In this assignment, we shall train a neural network to draw a curve. The curve takes one input variable, the…


Added by Sandipan Dey on May 31, 2018 at 10:00pm — No Comments

Image identification using a convolutional neural network

This blog  explores a typical image identification task using a convolutional ("Deep Learning") neural network. For this purpose we will use a simple JavaCNN packageby D.Persson, and make our example small and concise using the Python scripting language. This example can also be rewritten in Java, Groovy, JRuby or any scripting language supported by the Java virtual machine.

This example will use images in the grayscale format (PGM). The name "PGM" is an acronym derived from…


Added by jwork.ORG on May 31, 2018 at 1:30pm — No Comments

Bill Vorhies Retrospective: Part 2

Bill is the Editorial Director for Data Science Central, and President and Chief Data Scientist at Data-Magnum, providing predictive analytics and big data infrastructure projects as a service. Bill has been an active commercial predictive modeler since 2001.

Bill Vorhies

In this…


Added by Vincent Granville on May 31, 2018 at 5:00am — No Comments

Machine Learning with C++ - Polynomial Regression on GPU

Hello, this is my second article about how to use modern C++ for solving machine learning problems. This time I will show how to make a model for polynomial regression problem described in previous article, but now with another library which allows you to use your GPU easily.



Added by Kyrylo Kolodiazhnyi on May 30, 2018 at 1:30am — No Comments

Data Science: Lifecycle approach to data-driven value creation

Data science had broad applications across many different industries. 

If we focus on industries that are in the business of buying (some or all) of a company, then trying to improve the operations before selling then we can identify at least three critical stages for data science to play a significant role.

  1. Early Exploration: Mining databases for trend and customer insights
  2. Enhanced Pre-acquisition Analysis: Linking early exploration…

Added by Howard Friedman on May 29, 2018 at 9:00am — No Comments

Text Mining and Sentiment Analysis - A Primer

Over years, a crucial part of data-gathering behavior has revolved around what other people think.  With the constantly growing popularity and availability of opinion-driven resources such as personal blogs and online review sites, new challenges and opportunities are emerging as people have started using advanced technologies to make decisions now. Sentiment analysis or opinion mining, refers to the use of computational linguistics, text analytics and natural language processing to identify…


Added by Nishtha Saxena on May 29, 2018 at 2:30am — No Comments

Crypto-craze,, A Flavor of PrimeNet

In case you've missed it, there has been a tremendous number of news stories, social media posts and the like on Bitcoin, Hashing Algorithms, Blockchain, video graphics cards and Crypto-mining.  If you are anything like the most of us, the information barely provides you a platform to have a discussion about the topic.  But what does it all mean?  What is a…


Added by Richard Charles, PhD on May 28, 2018 at 12:30am — No Comments

Why GDPR will Make Machine Learning not so legal

GDPR & Our Data

All of sudden lawyers are busy and got lot of work to do on this new thing called as GDPR. Because 90% of the world’s data was created in the last two years. Will GDPR also going to impact historical data. Does GDPR require Machine Learning algorithms to explain their output? may be yes may be no or in short probably not, but there is enough ambiguity to be clarified and keep DataScientists, Lawyers, industry influencers busy.…

Added by Vinod Sharma on May 27, 2018 at 9:30pm — 2 Comments

Time-series data mining & applications

A time series is a sequence of data points recorded at specific time points - most often in regular time intervals (seconds, hours, days, months etc.). Every organization generates a high volume of data every single day – be it sales figure, revenue, traffic, or operating cost. Time series data mining can generate valuable information for long-term business decisions, yet they are underutilized in most organizations. Below is a list of few possible ways to…


Added by Mab Alam on May 27, 2018 at 9:00pm — No Comments

Seamless Customer Experience for Telecoms: A Practical Approach

In this age of data and convenience, customers across the globe are getting used to great customer experience from numerous companies. Big names such as Google, Apple, Amazon,…


Added by Ronald van Loon on May 27, 2018 at 9:00pm — No Comments

Go Ahead and Automate Jobs

Machine learning has the ability to automate a lot of jobs in the future. It is very easy to talk about this automation when it isn't your job that will be automated. But the scary part is that there are a lot of highly skilled jobs that will also face some type of automation in the future as well. When you are talking about your own job potentially being automated, it becomes less abstract and more real. It is very easy to say go ahead and automate jobs, until it is your own that is being…


Added by Ylan Kazi on May 27, 2018 at 11:30am — 2 Comments

Ecology of Metrics

Although I deal with many different types of metrics, I believe they can be generally classified as follows: 1) time use; 2) alignment; 3) production; 4) performance; 5) service; 6) and market.  In this blog, I will be providing some comments pertaining to each.  Although I have yet to encounter any myself, I am certain that there must be text books on the issue of operational metrics and how to make use of them.  However, I personally developed nearly all of those that I use.  Although I do…


Added by Don Philip Faithful on May 26, 2018 at 9:00am — No Comments

Weekly Digest, May 28

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


Added by Vincent Granville on May 26, 2018 at 8:00am — No Comments

Apache Hadoop Admin Tips and Tricks

In this post I will share some tips I learned after using the Apache Hadoop environment for some years, and  doing many many workshops and courses. The information here considers Apache Hadoop around version 2.9, but it could definably be extended to other similar versions.

These are considerations for when building or using a Hadoop cluster. Some are considerations over the Cloudera distribution. Anyway, hope it…


Added by Renata Ghisloti Duarte Souza Gra on May 24, 2018 at 5:00pm — No Comments

Data Science for Internet of Things - The Big Picture

This big picture view lays the foundation of our book Data Science for the Internet of Things. (Co-authored by Ajit Jaokar, Jean Jacques Bernard and Sukanya Mandal)

We address the question: at what points can we add analytics to the data after it leaves the sensor and what are the implications of doing so at various stages.



Added by ajit jaokar on May 24, 2018 at 4:00pm — 5 Comments

The First Things you Should Learn as a Data Scientist - Not what you Think

The list below is a (non-comprehensive) selection of what I believe should be taught first, in data science classes, based on 30 years of business experience. This is a follow up to my article Why logistic regression should be taught last.

I am not sure whether these topics below are even discussed in data camps or college…


Added by Vincent Granville on May 24, 2018 at 1:00pm — 9 Comments

Are YOU the Outlier?

AI and machine learning are everywhere. Most decisions affecting every aspect of our lives are being made based on anomalies, classifications, and predictions. Even governmental decisions such as where will new schools be built may consider an enormous amount of demographic, geographic, and socioeconomic data to determine exactly which land will house the school – and developers are using similar data to buy up the plots they think the governments will…

Added by David Maman on May 23, 2018 at 11:30pm — No Comments

Poker, Probability, Monte Carlo, and R

My daughter just started a business analytics Master's program. For the probability sequence of the core statistics course, one of her assignments is to calculate the probability of single 5 card draw poker hands from a 52-card…


Added by steve miller on May 23, 2018 at 11:30am — 2 Comments

What a CEO needs to know about Machine Learning algorithms

During my first project in McKinsey in 2011, I served the CEO of a bank regarding his small business strategy. I wanted to run a linear regression on the bank's data but my boss told me: "Don't do it. They don't understand statistics". (We did not use Machine Learning but, 7 years down the road, I still believe we developed the right…


Added by Pedro URIA RECIO on May 23, 2018 at 2:00am — No Comments

Are You Ready To Become A Chief Data Scientist?

You know who you are. A high-calibre machine learning magician, a well-versed wrangler of data... but you want a bit more from your role. That may be progression, more money or the chance to work on new, more exciting projects, but where do you go from here?


Many companies are looking to increase investment in data science departments and looking for leaders to build out new teams to do this. But before you take the plunge into the C-level, weigh up what this role entails and…


Added by Matt Reaney on May 23, 2018 at 1:00am — No Comments

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