Главная
Study mode:
on
1
Intro
2
Why Al Audits
3
Rise of the Citizen Data Scientist
4
Designing for Citizen Data Scientists
5
Wizard Driven, No-Code ML
6
Evaluation & Visualization
7
Business Benefits
8
Human in the Loop Anomaly Lifecycle
9
Deployment Options
10
Enterprise Tech Stack Integration
11
How the Solution Works
12
Cloud Native Serverless Architecture
13
Databricks Integration
Description:
Explore a cloud-native, wizard-driven AI anomaly detection solution in this 23-minute video from Databricks. Learn how Citizen Data Scientists can easily create models to flag various types of anomalies at the transaction level, including collusion between actors. Discover unsupervised and supervised modeling methods executed in Apache Spark on Databricks, and understand the innovative aggregation framework that converts fraud scores into actionable insights. Gain insights into the Anomaly Lifecycle, from statistical outlier to validated business fraud, and learn about Human-in-the-Loop feedback methods for continuous model improvement. Examine client success stories in the Pharmaceutical and Transportation industries, and explore the solution's deployment options, enterprise tech stack integration, and cloud-native serverless architecture with Databricks integration.

Wizard Driven AI Anomaly Detection with Databricks in Azure

Databricks
Add to list
0:00 / 0:00