In this workshop, we will develop custom neural networks for any data you might bring or any public datasets you might be interested in. We will start with learn theoretical concepts on deep learning and then dive deep into how you could use Abacus.AI to quickly train cutting edge, deep learning-based models, utilizing all or most of the theoretical concept you would have recently learned.
(I) Technical talk on deep learning core concepts like loss functions, dropout rate, batch size, learning rate, and etc...
(II) Demo where we will cover how to upload data, and then train, tune, deploy and finally generate predictions from your custom neural network.
(III) Build and deploy deep learning models for forecasting and recommendations
Agenda (US pacific time):
[10:00 - 10:10am] Welcome and workshop overview
[10:10 - 10:45am] Overview on deep learning core concepts
[10:45 - 11:45am] Hands on code labs (Recommender AI and Forecasting)
[11:45 - 12:00pm] 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
Yury is currently a machine learning research engineer, working on core components of forecasting modelling at Abacus.AI. He has a PhD degree from Caltech