3rd October 2019, Thursday
3pm Sydney | 1pm Singapore | 10.30am Mumbai
In this Deep Learning Fundamental Series Part 2, we will cover the principles for training your neural network including activation and loss functions, batch sizes, data normalization, and validation datasets.
All these concepts will be brought to life by demonstrating how Databricks simplifies deep learning - letting you quickly access ready-to-use ML environments, as well as prepare data, and train models faster. After this session, if requested, you will receive the presentation and associated notebooks so you can run the samples yourself.
Presenters
Denny Lee
Global Developer Advocate at Databricks
Denny Lee is a Global Developer Advocate at Databricks. He is a hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premise and cloud environments. He also has a Masters of Biomedical Informatics from Oregon Health and Sciences University and has architected and implemented powerful data solutions for enterprise Healthcare customers.