Enhancing ML App with Wisdom of the Crowd

Speaker: Angeline Yasodhara and Azin Asgarian, Applied Research Scientists at Georgian
Abstract:
As the deployment of Machine Learning (ML) models in the industry increase with the ever-increasing size and complexity of the datasets, the strategy used for developing and deploying these model becomes more crucial. A common strategy often used in AI companies is to train various ML models for solving different pieces of a bigger problem. But what is often missed is how these models can collaborate and help each other. Having a strong set of ML models is like having a strong team of experts. Each of them may be able to solve a very specific problem accurately, but together, they can solve even more challenging problems! In this talk, we will show you how various ensembling techniques can be used to enhance the performance of ML models on challenging problems while increasing the explainability and usability of the final solution!