Data Science Statistics Articles, Guide, and Tutorials

Data Science Projects, Tips for successful implementation

DataOps Modeling Statistics Tools & Languages Workflow Businessposted by Diego Arenas, ODSC January 10, 2018

This is the first post of a series of three articles in which we will discuss tips and guidelines for successful data science implementations. This post goes over the things you should worry about before to write the first line of code. A high level data... Read more

On Machine Learning and Programming Languages

Modeling Predictive Analytics Python R Statistics Tools Tools & Languages Juliaposted by Mike Innes December 13, 2017

This article was co-written by Mike Innes (Julia Computing), David Barber (UCL), Tim Besard (UGent), James Bradbury (Salesforce Research), Valentin Churavy (MIT), Simon Danisch (MIT), Alan Edelman (MIT), Stefan Karpinski (Julia Computing), Jon Malmaud (MIT), Jarrett Revels (MIT), Viral Shah (Julia Computing), Pontus Stenetorp (UCL) and... Read more

How To Do User Segmentation Right – A Practical Guide for Data Analysts

Conferences Modeling Statistics Webinarposted by ODSC Team December 7, 2017

What You Will Learn: The different ways to segment users Walk through a real-world segmentation exercise There are different ways to segment users – marketers and user researchers typically use the interview or survey methods and segment users based on attitudes or intentions. By contrast, data... Read more

How to Analyze Articles About Data Science Using Data Science

Modeling Statistics Clusteringposted by George McIntire, ODSC December 5, 2017

In a previous post, we demonstrated how to use the Python3 library Newspaper to painlessly extract data from news articles. Using Newspaper, I was able to extract text from over a 1000 articles about topics including, but limited to Data Science, Artificial Intelligence, and Big Data.... Read more

Visual Analytics of Instagram’s #gopro hashtag with AI

Data Visualization Modeling Statistics Deep Learningposted by Shashank Gupta December 5, 2017

Images have become a very common medium of human expression on the internet with the coming up of social networks. Facebook is the biggest repository of digital images ever. This trend is only going to intensify given the emergence of image first platforms like Instagram and... Read more

Some things I’d like you to know about Data Science

Data Wrangling DataOps Modeling Statistics Tools & Languages Introposted by Damon Civin December 1, 2017

Things I’ve learned mostly by making mistakes Masses of data + cutting edge machine learning + cheap compute = Profit. Right? It’s not that simple. Data science isn’t a replacement for asking difficult questions and doing hard work based on the answers. In fact, it’s quite the... Read more

Big aggregate queries can still violate privacy

Data Wrangling Modeling Statistics Privacyposted by John Cook November 26, 2017

Suppose you want to prevent your data science team from being able to find out information on individual customers, but you do want them to be able to get overall statistics. So you implement two policies. Data scientists can only query aggregate statistics, such as counts... Read more

Linked Data and Data Science

Modeling NLP/Text Analytics Statistics Tools Tools & Languagesposted by Diego Arenas, ODSC November 25, 2017

The capacity to connect any data source in the world is in our hands today, it’s what’s known as the Semantic Web or the Web of Data. The Internet had a clear orientation to be human-readable when it was invented, now we need it to be... Read more

Why conversion matters — a toy model

Modeling Statisticsposted by Erik Bernhardsson November 22, 2017

There are often close relationships between top level business metrics. For instance, it’s well known that retention has a super strong impact on the valuation of a subscription business. Or that the % of occupied seats is super important for an airline. A fun little toy... Read more

Lessons in data science/machine learning (mostly not taught in school)

Modeling Predictive Analytics Statisticsposted by ODSC Team November 22, 2017

Don’t start with a hammer. Find the nail first, then grab the right tool. Or, why technology alone is not enough. From a Fireside Chat at Galvanize SF, July 5 2017, with: Mark Meloon (Caltech, startups, teaches data science) Sean Gerrish (Princeton, Google) Yunkai Zhou (Tsinghua, Google) See below for... Read more