This week we completed four in-depth training webinars focused on WhizzML, BigML’s new domain-specific language for automating Machine Learning workflows, implementing high-level Machine Learning algorithms, and easily sharing them with others. We already have our first batch of WhizzML graduates merely a week after launch. However, many of you were either not able to secure a live webinar spot or not able to join us at the scheduled date and time. Don’t fret if you missed any of these training sessions. You can now watch the whole series at your own pace on BigML’s YouTube channel.
We suggest that you follow the same order in the series as there are dependencies that may slow down your comprehension if you skip things. Here is brief guide on how the series is structured:
1. Introduction to WhizzML
The first session covers all the basics describing how WhizzML is implemented on the BigML platform. Ryan Asensio, BigML’s Machine Learning Engineer, introduces the purpose of the language and some benefits over other ways of implementing Machine Learning workflows and algorithms.
2. Language Overview and Basic Workflows
This intermediate webinar explores the WhizzML domain-specific language in greater detail, with a whirlwind tour of its syntax, programming constructs and basic standard library functions. In this second training session, Charles Parker, BigML’s VP of Machine Learning Algorithms, explains how to create and use WhizzML resources (libraries, scripts and executions) by means of several simple yet fully functional example workflows.
3. Advanced Machine Learning Workflows
The third training session is an advanced webinar where we continue our exploration of the WhizzML language, diving into more complex examples and using more advanced features of the language. Charles Parker, BigML’s VP of Machine Learning Algorithms, explains how some of the most effective Machine Learning algorithms can be implemented and automated on top of the BigML with WhizzML.
4. Real-world Machine Learning Workflows
In the fourth session, Poul Petersen, BigML’s Chief Infrastructure Officer, walks you through some real-world workflow automations with an eye towards the kind of problems posed by complex use cases. In this advanced webinar we use some of the best tricks to solve your Machine Learning problems with confidence.
You can always visit the dedicated WhizzML landing page for the most up to date info and resources.
Have an idea for a new script for a Machine Learning task? As always, forward us your questions or comments anytime at firstname.lastname@example.org. We are looking forward to hear about the Machine Learning projects that you are looking to automate.