Blog

Immediately after PAPIs.io '14 I spent a couple of days at Strata in Barcelona. Strata has several tracks and I ended up going mostly to “business” sessions, but this synthesis of things I heard at the conference will be of interest to technical people as well. Actually there was one business session that had more code in it than another data science session I went to!

Here is my selection of key take-away messages, from sessions I attended (Strata is a huge conference so this is just a very partial view of it):

• Make predictions that you can act on
• When hitting a performance plateau, use new data — not fancier algorithms
• Ensuring your work is reproducible has never been easier — now make it your habit
• Getting a business edge with data requires automating decisions

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Big data startup Qucit released this month the world’s first bikeshare predictive API, tightly integrated in the popular mobile app for Bordeaux bikes. This is an inspiring example of Machine Learning usage in the real world. One of the value propositions of Predictive is better resource management. Here, in the "smart city" context, it impacts our everyday lives.

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Last week I visited the Import.io offices in London and did a webinar with them in which I showed:

• how to use their tool to easily scrape real estate data from the web
• how to clean that data with the Pandas library in Python
• how to build a real-estate pricing model by sending the clean data to BigML.

Check out the video recording and the write-up they did!

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I will be chairing the PAPIs.io conference taking place on 17-18 November 2014 in Barcelona, right before Strata. It will be the first ever international conference dedicated to Predictive APIs and Predictive Apps. If you're interested in presenting your work in this space, a Call for Proposals is open until 8 October 2014.

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As machine learning and predictive analytics services become more widely embraced in the business world, predictive APIs are starting to open up. When evaluating this class of API, it is useful to have a common set of questions — the answers to which will help determine whether prediction APIs are a good fit for your needs and to steer you toward the best product for your organization.

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I am proud to announce that I have teamed up with HumanCoders to set up a groundbreaking Machine Learning training program which is based on Prediction APIs and brings you up to speed in 3 days. At this occasion, they interviewed me and I gave them 3 copies of my book, Bootstrapping Machine Learning, to give away — here's your chance to snatch one of them!

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Churn prediction is one of the most popular Big Data use cases in business. It consists of detecting customers who are likely to cancel a subscription to a service. Although originally a telco giant thing, this concerns businesses of all sizes, including startups. The problem of churn prediction can be tackled with machine learning techniques. Now, thanks to prediction services and APIs, this sort of predictive analytics is no longer exclusive to big players that can afford to hire teams of data scientists.

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