— In the News —
Great article by Matt Turck from FirstMark Capital on the business of selling data. If you’re one of the many startups sitting on a growing data asset and trying to figure out whether you can make money selling it to Wall Street, this post is for you: a deep dive to provide context, clarify concepts and offer some practical tips.
The ability of statistics to accurately represent the world is declining. In its wake, a new age of big data controlled by private companies is taking over – and putting democracy in peril.
The work could lead to a new approach to the study of what is possible, and how it follows from what already exists.
— Sponsored Link —
Find out why 88% of companies that regularly exceed growth and profit expectations use a centralized platform to do data science work. DataScience’s upcoming webinar features Forrester VP and Principal Analyst Brian Hopkins, who will share the practices, tools, and attributes that define leading data science companies. Register now.
— Tools and Techniques —
This best practices guide is a nice collection of practical tips for applying Machine Learning in the real-world. This was written by Martin Zinkevich, a Google Research Scientist, and is intended for a broad audience of Machine Learning students and engineers.
Building a data team is a challenge anywhere but there are some questions that startups, in particular, have to consider. This is a great Quora answer by Monica Rogati, a former data scientist at LinkedIn and VP of Data at Jawbone.
There are a lot of tutorials about how decision trees work. Here's why they work.
This is the final post in a popular series about building a Data Science Portfolio.