Join the 73,000+ customers using BigML, the ideal platform to master Machine Learning.
Machine Learning has infinite potential to do good, but it has been historically underutilized outside the confines of the few privileged with advanced technical degrees and access to specialized hardware. BigML is actively changing this by lowering the barriers of entry to make Machine Learning accessible for everyone. Today, we help thousands of analysts, software developers, and scientists around the world to solve Machine Learning problems "end-to-end" regardless if they have prior experience in Machine Learning.
BigML has grown through grassroots adoption since our founding in 2011, reaching important milestones along the way. Within less than a year of our public launch of Machine Learning as a Service, BigML had over 3,000 registered customers. In August 2017, we passed a new milestone of 50,000 registered customers who represent organizations of all sizes and industries. Find out from satisfied customers around the world in their own words.
VSSML17 was a perfect opportunity to get high-level context beyond the standard predictive palette we use at Faraday. But it was also helpful to focus in on the implications of new tools and methods that BigML is bringing online, and to get facetime with the team that's driving it all.
BigML makes Machine Learning easy with its intuitive design. Data can be analyzed in seconds without the hassle of writing code. As Machine Learning becomes more important for me, I trust BigML to keep the process easy and informative while staying up to date on the latest advancements in Machine Learning.
We use BigML for our introductory data mining class of 200-300 students annually since 2014. BigML stands out from the competition with its superb model visualizations, lean user interface, worry-free maintenance, and reliability.
BigML made it easy for me to get started with Machine Learning. It is very intuitive and the structure of the process is easy to understand. I also like the interactive visualization of my data and the possibility to experiment with different filters and options.