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  • Data Scientists, Data Engineers, Software Engineers: The Difference According to LinkedIn

    Data Scientists, Data Engineers, Software Engineers: The Difference According to LinkedIn

    The differences between Data Scientists, Data Engineers, and Software engineers can get a little confusing at times. Thus, here is a guest post provided by Jake Stein, CEO at Stitch formerly RJ Metrics, which aims to clear up some of that confusion based upon LinkedIn data. As data grows, so does the expertise needed to… Read more

  • Know Your Probability Distributions

    In data science and statistics, probability distributions can be very important. I have been meaning to create a listing of them. However, I no longer need to since the fine folks at Cloudera have already created a list at Common Probability Distributions: The Data Scientist’s Crib Sheet. Learn the distributions and pick a favorite. (My… Read more

  • Our World In Data

    Our World in Data is data visualization site for exploring the history of civilization. The site was created by Max Roser. Our World in Data contains tons of information about many aspects of people’s lives. It also includes numerous visuals (like the one below) which can be easily shared or embedded on other sites. https://ourworldindata.org/grapher/life-expectancy… Read more

  • Data Science and the Perfect Team

    Data Science and the Perfect Team

    Today, I am proud to welcome a guest post by Claire Gilbert, Data Analyst at Gongos. For more on Gongos, see the description at the end of the post. It’s fair to say that for those who run in business intelligence circles, many admire the work of Fast Forward Labs CEO and Founder Hilary Mason.… Read more

  • Recent Resources for Open Data

    Recently, a number of resources for publicly available datasets have been announced. Kaggle becomes the place for Open Data – I think this is big news! Kaggle just announced Kaggle Datasets which aims to be a repository for publicly available datasets. This is great for organizations that want to release data, but do not necessarily… Read more

  • Data Science Ethical Framework

    The UK government has taken the first step in providing a solid grounding for the future of data science ethics. Recently, they published a “beta” version of the Data Science Ethical Framework. The framework is based around 6 clear principles: Start with clear user need and public benefit Use data and tools which have the… Read more

  • Machine Learning Yearning Book

    Andrew Ng [Co-Founder of Coursera, Stanford Professor, Chief Scientist at Baidu, and All-Around Machine Learning Expert] is writing a book during the summer of 2016. The book is titled, Machine Learning Yearning. It you visit the site and signup quickly you can get draft copies of the chapters as they become available. Andrew is an… Read more

  • How to Kickstart Your Data Science Career

    This is a guest post from Michael Li of The Data Incubator. The The Data Incubator runs a free eight week data science fellowship to help transition their Fellows from Academia to Industry. This post runs through some of the toolsets you’ll need to know to kickstart your Data Science Career. If you’re an aspiring… Read more

  • Berkeley Undergrad Data Science Course and Textbook

    The University of California at Berkeley has started The Berkeley Data Science Education Program. The goal is to build a data science education program throughout the next several years by engaging faculty and students from across the campus. The introductory data science course is targeting freshman and it is taught from a very applicable and… Read more

  • A Couple of Current Data Science Competitions

    Decoding Brain Signals Microsoft has recently announced a machine learning competition platform. As part of the launch, one of the first competitions is the prediction of brain signals. It has $5000 in prizes, and submissions are accepted thru June 30, 2016. Big Data Viz Challenge Google and Tableau have teamed up to offer a big… Read more

  • Free Stats book for Computer Scientists

    Professor Norm Matloff from the University of California, Davis has published From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science which is an open textbook. It approaches statistics from a computer science perspective. Dr. Matloff has been both a professor of statistics and computer science so he is well suited to write such… Read more

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Data Science 101

One of the oldest blogs on data science, started in 2012.

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