Get Started with Deep Learning
Deep learning model performance is known for scaling well with data size, but training these models can be notoriously time-consuming. As more companies adopt deep learning, the need for using distributed deep learning frameworks becomes more important than ever.
In this webinar, we’ll share:
- How distributed deep learning works and give you an overview of the different frameworks including TensorFlow, Keras and Pytorch.
- How Databricks is making it easy for data scientists to migrate their single-machine workloads to distributed workloads, at all stages of a deep learning project.
- A demo of distributed deep learning training using our newly released feature, HorovodRunner.
Yifan Cao, Senior Product Manager, Databricks
Yifan Cao is a Senior Product Manager at Databricks. His product area spans ML/DL algorithms and Databricks Runtime for Machine Learning. Prior to Databricks, Yifan worked on two Machine Learning products, applying NLP to find metadata and applying machine learning to predict equipment failures. He helped build the products from ground up to multi-million dollars in ARR. Yifan started his career as a researcher in quantum computing. Yifan received his B.S in UC Berkeley and Master from MIT.