Before implementing a program, I like to first develop a logic model.  

This can be a fast exercise that can lead to insights into the strengths and weaknesses of the program design.  There are many different models used and I prefer a simple one with 4 basic parts:

1. Inputs—resources that go into a program including staff, materials, money, equipment, facilities,…

This article was written for The Data Incubator by Jay Kaiser, a Fellow of our 2018 Winter cohort in Washington, DC.

The Question

The 2016 Presidential Election was, in a single word, weird. So much happened…

This article comes from Deep Learning Patterns. 

Note to reader: Diving into this material here can be a bit overwhelming. One way though to get an understanding of the thought process is to follow the Intuition Machine blog. 

Deep Learning Architecture can…

We discuss a new approach for selecting features from a large set of features, in an unsupervised machine learning framework. In supervised learning such as linear regression or supervised clustering, it is possible to test the predicting power of a set of features (also called independent variables by statisticians, or predictors) using metrics such as goodness of fit with the response (the dependent variable), for instance using the R-squared coefficient. This makes the process of feature…

In business, we often implement programs and then try to determine if the program had an impact. This is an example of program evaluation where, more generally, program evaluation is a study conducted with the intent of determining how effective a given intervention (program) is at achieving a specific outcome.

What types of programs? That could be a cross-sell program, customer retention program, new advertising method etc.

Is this just A/ B testing? A/B testing is a great…

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.

In this series consisting  of six parts so far (and…

Abstract

In this study, we predict the outcome of the football matches in the FIFA World Cup 2018 to be held in Russia this summer. We do this using classification models over a dataset of historic football results that includes attributes from the playing teams by rating them in attack, midfield, defence, aggression, pressure, chance creation and building ability. This last training data was a result of merging international matches results with AE games ratings of the teams…

Summary: Computational Synthetic Biology (CSB) is likely to be both the next big thing and perhaps most important field to exploit data science.  As the name implies, this lies at the intersection of data science and biological research.  Big advancements and big investments are already starting to occur here.  Data scientists with deep learning skills will want to check this out.

 …

Credits: Google Images

This is the story from time when I was in initial years of my programming career and I was a huge fan of Jetbrains IDE’s (I am still), I was using Windows prominently at that…

Most of you reading this are probably more used to playing online casino games using real money. It's money you’ve earned, transferred from your bank account into your casino account. You could walk out right now, go to an ATM and withdraw it. What you’re not probably used to is using cryptocurrency for crypto coin casinos. In fact, you might not even know that cryptocurrency casinos are a thing that…

Previously, we looked at how Artificial Intelligence (AI) has changed the supplier side of the retail eco-system, especially on two fronts – Price and Product Offering. In this post, we shall analyze how it has affected the buyer’s journey at almost every step of the way.

As most of you will know, a buyer’s journey starts from the awareness stage, where he…

C-3PO and R2-D2 are an odd couple in the Star Wars universe. C-3PO is a cowardly droid who obeys pre-defined protocols and routine tasks, while R2-D2 is a curious and adventurous robot who learns from previous problems, uses logical thinking and larger concepts to solve new problems. But together they do things they could not do alone.

Similarly, RPA…

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.

Announcements

• In a live webinar on June 21 at 2PM CT, watch Anaconda Data Scientist Tom Augspurger demonstrate how dask enables analysis of large datasets in parallel, using all the cores…

In my most recent blog, I discussed the idea of aligning the supply of services to market demand.  My conceptualization of “alignment” specifically relates to time intervals: i.e. having people at the right place and at the right time - for example, to take advantage of opportunities - is a sign of alignment.  Alignment for me is often about the relationship between capacity and incapacity:  the ability to supply services versus the inability to satisfy the market demand…

A few years ago, the impact of digitization was only established in top industries like Banking, Insurance, and Retail. Now times have changed – the recruitment industry is also adopting digital transformation.

Everyone is a candidate at some point in their journey. Whether you are an employer or a candidate…

The book "Mastering Machine Learning Algorithms" has been published by Packt 

From the back cover:

Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more…

This article was published by Andre De Castro on Blockgeeks. Andre is the CEO & Co-Founder of Blockchain of Things, Inc. 

Blockchain has become a media buzz due to its unique and powerful qualities. While a lot of excitement exists for its use in both financial and identity applications, a new and more exciting area for this technology has emerged. It is …

This article was written by Monica Rogati. Monica is an independent data science executive and advisor. She built key data products and teams at Jawbone and LinkedIn; she now helps companies make the most out of their data.

Do a project you care about. Make it good and share it.

There’s a lot of interest in becoming a data scientist, and for good reasons: high impact, high job satisfaction, high salaries,…

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

• How are We Changing the Internet? How is the Internet Changing Us? 
• Be a Social Data Scientist – It is Good Karma! …