2016 is the year of Deep Learning, whose popularity has been on a steep incline ever since Google bought DeepMind at the end of 2014. Last year’s technical breakthroughs, acquisitions, funding deals and, open source releases have all helped to cement Deep Learning as the hip artificial intelligence. Our CTO, Matt Painter, explains…
We are pleased to announce that Import.io (that’s us btw) has just raised a $13 million Series A round of funding. The new investment was led by Imperial Innovations, with participation from Wellington Partners, Oxford Capital, Open Ocean, Delin Capital and AME Cloud Ventures. “This new round of funding represents the…
Kaggle has become the premier Data Science competition where the best and the brightest turn out in droves – Kaggle has more than 400,000 users – to try and claim the glory. With so many Data Scientists vying to win each competition (around 100,000 entries/month), prospective entrants can use all…
Start the new year off right by making sure your Big Data team is aligned Today’s business leaders need a way to effectively utilize big data analytics to improve their companies. That means having the best people on the job as part of a data team designed to derive…
Ok, let’s start with the basics. Leads represent the first stage of the sales process. In its simplest form a lead is any “person or entity that has an interest and authority to purchase your product or service”. Or in other words: someone you can sell to.
Sounds good. So, what information do you need about that person or entity for it to be an actionable lead? A good rule of thumb is to look for the information that you would find on a business card, i.e. their name, associated company and contact details.
Oxfam making Headlines The data team at Oxfam used data to show that Britain’s five richest families are worth more than the poorest 20% and lobby for policy change. Proving that just one simple data set can start something huge. Read more in The Guardian
Two weeks ago the UK’s Office of National Statistics (ONS) announced that the UK economy had grown by 0.9% in the second quarter of 2014. This growth was partly due to the decision to include prostitution in gross domestic product (GDP) for the first time ever.
The ONS estimate that Britain’s 60,879 prostitutes contribute £5.314bn (0.4% GDP) to the UK economy. But, this figure completely ignores male prostitution. In a previous post we used data from AdultWork, a popular sex worker website, to determine that 42% of UK prostitutes are male, which (all other factors being equal) represents an additional £3.542bn of UK GDP!
Our initial analysis was very simple, but nonetheless raised a lot of interest from you all, along with some great questions about the gender differences between male and female sex workers. We decided to look a little deeper into the gender differences amongst sex workers online and this is what we found.
