In this workshop, we will discuss both theoretical concepts on deep learning, data preparation, automl and hand-on code labs.
Learn how to do enterprise scale data preparation, ETL and configure custom neural networks and apply to real-world problems such as predictive modeling, forecasting and personalization
We will start with a technical talk on deep learning core concepts like loss functions, dropout rate, batch size, learning rate, and etc...
Then we will walk through 2 real world use-cases - Churn Reduction and Lead Scoring. We will take data from multiple sources, understand the data prep required and than craft custom neural networks for each case
Welcome and workshop overview
Overview on deep learning automl core concepts
Hands on code lab
Q&A and wrap up
Head of Content & Developer Relations at abcuas.ai
CEO and Co-Founder of Abacus.AI. she was the General Manager for AI Verticals at AWS, AI. Her organization created and launched Amazon Personalize and Amazon Forecast, the first of their kind AI services that enable organizations to create custom deep-learning models easily. Prior to that, she was the CEO and co-founder of Post Intelligence that was acquired by Uber. Bindu was previously at Google