Machine Learning usage in the industry is fairly nascent with most practitioners gaining expertise through online courses and working mostly within the confines of a colab. When the same practitioner is tasked with designing and deploying their first ML system, they often make the mistake of focusing entirely on the model development part and their local development environment where training rather than inference is the bottleneck; resulting in culture shock and a steep learning curve getting the model deployed to production
The objective of this webinar is to prepare the practitioner for the inevitable culture shock and minimize the learning curve by instilling production best practices that tech giants adhere to. We will present a detailed overview of the design and architectural choices behind Uber’s Michelangelo: The full-stack ML ecosystem empowering hundreds of engineers and analysts to deploy thousands of models daily.
The Certificate of Participation will be provided from CloudxLab to all the attendees.
Here is the link for Git repository -https://github.com/cloudxlab