Deep Dive into Data Science with Snowflake
This session will give you a in depth walkthrough on how you can use Snowflake across key stages of the data science workflow. The session will show you how to preparing your data within Snowflake using SQL, Java, Scala or Python, before exploring building models with your machine learning (ML) platform of choice, and concluding with deploying ML models using UDFs.
We'll explore how the Data Cloud helps data scientists address their most common challenges, so they can focus their time and effort on solving complex data problems.
Data Scientist, Data Engineers, Analysts
Participant’s ROI (what you will take away):
- How to bring nearly all types of data into your model without complex pipelines.
- Augment model performance with shared data sets from your business ecosystem and third-party data from Snowflake Data Marketplace.
- Accelerate data preparation for any amount of data or users with Snowflake’s multi-cluster compute architecture thanks to autoscaling and near-zero manual operations
- Introduction to Snowflake Data Cloud
- How Snowflake built in functionality simplify data management for Data Science
- How to do Feature Engineering with Snowflake using the recently released Snowpark
- How to train Machine Learning models with your platform of choice
- How to deploy models to Snowflake for Machine Learning inference