The Need for Machine Learning is Everywhere!

In my work, which is predominantly information technology, the need for Machine Learning is everywhere. And I don’t mean just in the somewhat obvious ways like security or log file analysis. Consider, my work experience goes back to the tail end of the mainframe era. In fact one of my first jobs was networking together what were at the time considered powerful desktop computers as part of a pilot project to replace a mainframe. Since then Continue reading →
Posted in BigML | Leave a comment

The Importance of Feature Engineering

When people first see a demo of BigML, there is often a sense that it is magical. The surprise likely stems from the fact that this isn’t how people are accustomed to computers working; rather than acting like a calculator creating a fixed outcome... Continue reading →
Posted in BigML | Leave a comment

Big Data Spain Presentation

I was invited to give a talk at Big Data Spain in Madrid, Spain on November 18. If you are keeping track, I was in Barcelona at PAPIs.io the previous day, and even worse I hadn’t slept more than 4 hours in the previous 3 days between traveling, presenting, and preparing to present.… Continue reading →

Posted in BigML | Leave a comment

PAPIs.io 2014 Presentation

I had the opportunity to present a demo of BigML at the first Predictive APIs conference in Barcelona, Spain. I was the very first speaker on the very first day and other than a few problems with the WiFi dropping out on me and the difficulty reading the terminal during the API demo, everything went well.… Continue reading →

Posted in BigML | Leave a comment

Data Science Melbourne Meetup

After we launched BigML in Australia, we spent two weeks in Melbourne touring, giving demos, and talking to potential customers. One of the great venues I was invited to was the Data Science Melbourne meetup. They recorded the talk and made it available on youtube.… Continue reading →

Posted in BigML | Leave a comment

BigML Late Summer 2014 Webinar – Anomaly Detection!

Things at https://bigml.com were busier than ever in 2014, and by mid-year we had already introduced a second machine learning algorithm with our new Anomaly Detector, based on Isolation Forests. Of course there was also a bunch of other new features as well:

– Model Clusters
– Missing Splits
– Anomaly Detector
… And a tease for a few upcoming things:

– Sample Server
– Dynamic Scatterplot
– Projects

Continue reading →

Posted in BigML | Leave a comment

The Value of Things (VoT): MassTLC IoT Conference Panel

I was invited to speak on a panel at the MassTLC VoT conference in June. The topic of the panel was “Analyzing data to get actionable intelligence” which was a perfect opportunity to discuss the applicability of Machine Learning to the analysis of the data deluge that the Internet of Things will likely bring.… Continue reading →

Posted in BigML | Leave a comment

BigML Spring 2014 Webinar – Clustering!

This webinar introduced BigML’s K-means clustering algorithm, which was our first unsupervised learning algorithm. I worked hard on this webinar to come up with several easy-to-demonstrate applications of clustering. One of the coolest thing though is our Model Clusters feature which is a great way to “discover” the rules that describe each individual group in the cluster.… Continue reading →

Posted in BigML | Leave a comment

BigML API Webinar Mar 2014

This is the API webinar are promised at the end of the previous webinar when I was talking about “Programmatic ML”. I think it’s really important that even though BigML has such an excellent User Interface, BigML is an API first company; we export the same API at bigml.io that we use internally for our own UI.… Continue reading →

Posted in BigML | Leave a comment

BigML Webinar, January 28, 2014: Winter 2014 Release

This is the second BigML webinar – I got a little more technical with this one and used real data from Prosper. It’s pretty amazing the pace at which we implement new features; it had only been a few months since the last webinar and we brought:

Dataset filtering
Training weights
Adding dataset fields including Flatline
Node Threshold
Multi-Datasets
Batch Predictions
In-memory trees
… and of course the Development free tier

 … Continue reading →

Posted in BigML | Leave a comment