Overview of Automated ML June 2019

Explore automated machine learning (AutoML) in this 50-minute conference talk from the PASS Data Community Summit. Discover how AutoML automates feature engineering, algorithm selection, and hyperparameter tuning to find optimal models for your data. Learn about recent AutoML technologies, particularly for Azure, with demonstrations focusing on Python implementation using Azure ML Service and Azure Databricks. Gain insights into time series forecasting, data skewness, sample data handling, and working with Azure Workspace. Dive into practical aspects like creating experiments, diagnostics, and regression analysis. Understand AutoML's potential in accelerating, democratizing, and scaling AI development. Access accompanying slides on SlideShare for a comprehensive overview of the presentation content.

Poll
Agenda
Automated ML
Time Series Forecasting
Automated ML Demo
Automated ML Questions
Advanced Settings
Data Skewness
Sample Data
Computes
Repositories
Data bricks
Data bricks features
Demo
Notebook
Warnings
Azure Workspace
Authentication
Local Environment
Creating Experiment
Diagnostics
Auto Read File
Auto ML
Regression
Retrieval
Light Edge
Question
GitHub
AutoML
Support
Conclusion