Level Up Your ML Lifecycle: An Innovative, Modularized Approach

How does an image-processing application that classifies animals accelerate the development of a vehicle license plate number detector?
In this talk, Yaqi Chen, Lead Data Scientist at Object Computing, Inc., demonstrates how ML practitioners can achieve a level of scalability and generalization that opens up a vast landscape of possibilities. Using a real-world example, she illustrates how a series of plug-and-play modules built across the data, model, and deployment stages dramatically simplify the process of building an end-to-end ML project.
If you could benefit from an ML lifecycle framework that allows you to continue tackling complicated real-world challenges, while enjoying shorter development time, simplified bug isolation, and a cleaner code base, this talk is for you!