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A computer was asked to predict which start-ups would be successful. The results were astonishing
In 2009, Ira Sager of Businessweek magazine set a challenge for Quid AI’s CEO Bob Goodson: programme a computer to pick 50 unheard of companies that are set to rock the world. The domain of picking “start-up winners” was – and largely still is – dominated... Read more
ODSC East Interviews: Shir Meir Lador
The following Q&A is part of a series of interviews conducted with speakers at the 2017 ODSC East conference in Boston. This interview is with Shir Meir Labor, Lead Data Scientist at Bluevine, whose talk was entitled “Fraud Detection Challenges and Data Skepticism. The transcript has been edited... Read more
Simulation of empirical Bayesian methods (using baseball statistics)
Previously in this series: The beta distribution Empirical Bayes estimation Credible intervals The Bayesian approach to false discovery rates Bayesian A/B testing Beta-binomial regression Understanding empirical Bayesian hierarchical modeling Mixture models and expectation-maximization The ebbr package We’re approaching the end of this series on empirical Bayesian... Read more
Come see Anshuman Guha, Data Scientist from Spark Cognition Speak at ODSC West.  Standardizing Software Boundaries Let’s imagine a scenario where a picture sharing company has an app that allows users to purchase pictures and have them printed and shipped via a postal service. Each module of... Read more
Actuaries are bringing Netflix-like predictive modeling to health care
I’m an actuary. That means I use numbers to try to understand human behavior, manage risk, and evaluate the likelihood that a particular thing will happen in the future. Most people associate my work with green eyeshades and the morbid business of predicting how long someone... Read more
Push Your Analytics Out to Customers
Analytics and big data have penetrated most large organizations by now, and are helping to improve many internal decisions. But they can also have a major impact on the decisions of customers or citizens. This applies not only to decisions about what products to buy, but... Read more
Time series classification with Tensorflow
Time-series data arise in many fields including finance, signal processing, speech recognition and medicine. A standard approach to time-series problems usually requires manual engineering of features which can then be fed into a machine learning algorithm. Engineering of features generally requires some  domain knowledge of the... Read more
3 Powerful Applications of Using Analytics-as-a-Service
Analytics-as-a-Service is the combination of analytics software and cloud technology. Instead of hosting any analytics software on premises using your own servers, you use a ready-to-go solution that is easy to deploy and most of the time has a pay-as-you-go payment system. It is part of... Read more
Streaming Analytics better than Classic Batch, When and Why? – PART 1
While a lot of problems can be solved in batch, the stream-processing approach can give you even more benefits. In this blog post series we’ll discuss a real-world example of user session analytics to give you a use-case driven overview of business and technical problems that... Read more
Data Science, AI, Machine Learning Cheat Sheets
A curated set of resources for artificial intelligence (AI), machine learning, data science, big data, internet of things (IoT), and more.   Python Pandas Cheat Sheet – Python for Data Science NumPy Cheat Sheet – Python for Data Science Bokeh Cheat Sheet – DataCamp PySpark Cheat... Read more