Recapping BigML’s 2018 in Numbers

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Another year has gone by in a hurry in the Machine Learning world of BigML. 2018 saw the interest in Machine Learning from all industries continually get stronger. Not only are we seeing an increase in the level of awareness and sophistication towards productive business applications running existing processes more efficiently, but we’re also witnessing novel use cases turning Machine Learning into an all together strategic asset. When things happen so fast, one can sometimes find it a challenge to stop and reflect on milestones and achievements. So below are the highlights of what made 2018 another special year for us.


In 2018, the BigML platform crossed the 80,000 registrations mark worldwide adding to our milestones since inception in 2011. Our users keep making a difference in their workplaces, government agencies, as well as educational institutions all over the map putting the BigML platform to use in the most creative ways.

5 Major Releases + 23 Enhancements

2018 saw a wealth of new features on BigML opening up many more compositional workflows involving the collective resources and the corresponding API endpoints.

  • The year started out with the Operating Thresholds and Organizations capabilities being launched. Operating Thresholds let you better adjust the tradeoff between false positives and false negatives in your classification models while Organizations help assign different roles and privileges to different users in workgroups respectively.
  • The OptiML release followed, complementing an already impressive array of supervised learning resources for tackling classification and regression problems by applying Bayesian Parameter Optimization.
  • Our Fusions release gave the platform a whole new dimension allowing users to easily mix and match multiple models into an ensemble regardless if the underlying algorithms are different.
  • Keeping the momentum alive we launched Data Transformations, a much-requested collection of new features that let users manipulate and pre-process their data into a Machine Learning-ready format even without any SQL expertise.
  • Finally, Principal Component Analysis (PCA) will mark the year-end addition that extends BigML with a practical dimensionality reduction functionality adaptable to all types of input data e.g., categorical, numeric, text.


Aside from major releases, we made 23 smaller but noteworthy improvements to the BigML platform including but not limited to: Feature Engineering with Flatline Editor, Sliding WindowsSQL in the BigML API, New Text Analysis Options, Prediction Explanation and many more. You can find a full list of enhancements on our What’s New page in case you’d like to try out the ones you may have missed.

As usual, we’ve also kept BigML Tools updated to make sure insights from BigML resources find their way to different platforms. One such example is the newest version of our Predict App for Zapier, which allows you to easily automate your Machine Learning workflows without any coding by importing your data in real-time from the most popular web apps.

Making Enterprise Machine Learning accessible with BigML Lite

We also need to drop a special mention for BigML Lite, which is the latest addition to BigML’s product line up.

BigML Lite offers a fast-track route for implementing your first use cases. Ideal to get immediate value for startups, small to mid-size enterprises or in a single department of a large enterprise ready to benefit from Machine Learning with their first predictive use cases. Now, for as low as $10,000/year, any of these scenarios can be realized as a stepping stone to company-wide Machine Learning initiatives with a larger scope.

BigML Dashboard in Chinese

Part of being a global company as seen in the body of users representing 182 countries in 6 continents is recognizing the need to customize the user experience to match local expectations.

In 2018, as a result of growing demand in Asia, BigML has taken a giant step by translating the BigML Dashboard to Chinese. You can expect further local customization options down the road as we strive to delight our global users.

498,849 Code Changes through 225 Deploys!

All our releases and the new features were made possible due to some serious heavy lifting by our product development group, which make up a large percentage of our 33 FTE strong BigML Team.  Just to give a glimpse of the level of non-stop activity, our team updated our backend codebase 282,786 times, API codebase 41,413 times and our Web codebase 174,650 times. These improvements and additions were carried out through 225 production deployments dotting the entire year.


58 Events in 5 Continents

It’s hard to match the excitement of connecting with BigMLers during real-life events to hear their stories and receive their feedback. In 2018, we continued the tradition of organizing and delivering Machine Learning schools with VSSML18 and added to the rotation the Machine Learning School in Doha 2018 with record attendance. Next year, Seville will be also part of the ML education circuit with MLSEV.

On the industry-specific events side, the 2ML event held in Madrid, Spain, has been fruitful so we intend to continue this collaboration with Barrabes in the 2019 edition. To kick off the new year, we’ll make a stop in Edinburgh, Scotland in January sharing our experiences in automating decision making for businesses.


171 Ambassador Applications, 7 Certification Batches

Our Education Program saw continued growth in 2018, with the addition of 171 new applicants to help promote Machine Learning on their campuses, having 265 in total since we launched the Education Program. BigML Ambassadors span the globe and include students as well as educators. To boot, as part of BigML’s Internship Program, we’ve hired 3 interns that made valuable contributions. We are thrilled to see a continually increasing interest in gaining hands-on Machine Learning experience, having received hundreds of applications for internships and full-time positions throughout the year.learnml_2018

Moreover, in its second year of existence, our team of expert Machine Learning instructors completed 7 rounds of BigML’s Certification Program passing on their deep expertise to newly minted BigML Engineers.

BigML Preferred Partner Program

Last but not least is the new BigML Preferred Partner Program that we announced in the last quarter of 2018. With 3 levels and different rewards, it enables new synergies covering multiple sales and project delivery collaboration scenarios.

Our first announcement on that front involved Jidoka, a leader in RPA (Robotic Process Automation), and earlier this week we have revealed our partnership with SlicingDice, which offers a highly performant all-in-one data warehouse service that will in the near future come with built-in Machine Learning capabilities. Stay tuned for more partnership announcements in the new year as we’re in discussion with an exciting lineup of new BigML partners that will each make a difference in their respective industry verticals.

84 Blog Posts (so far)

We’ve kept our blog running on all cylinders throughout the year. 84 new posts were added to our blog, which has long been recognized as one of the Top 20 Machine Learning blogs. Below is a selection of posts that were popular on our social media channels in case you’re interested in catching up with some Machine Learning reading during the holidays.


Looking Forward to 2019

Hope this post gave a good tour of what’s been happening around our neck of the woods. We fully intend to continue carrying the Machine Learning for everyone flag in the new year. As part of our commitment to democratize Machine Learning by making it simple and beautiful for everyone, we will be sharing more of our insights, customer success stories, and all the new features we will bring you with each new release in 2019. As always, thanks for being part of BigML’s journey!

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