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Building an Operational Machine Learning Organization from Zero and Leveraging ML for Crypto Security

On Demand

Type

  • Session

Format

  • Hybrid

Track

  • Industry and Business Use Cases

Industry

  • Financial Services

Difficulty

  • Intermediate

Room

  • Moscone South | Upper Mezzanine | 159

Duration

  • 35 min
Download session slides

Overview

Introduction to BlockFi and what we do as a crypto company.
Our journey with Databricks:
- Building a cross functional ML team
- Scoping business problems to get executive buy in
- Conveying a strategic vision for ML at your organization
- Operationalizing ML & Data Science to solve business challenges
- Building clear business objectives for your ML Projects

Blockchain Analytics for security and risk identification
- Unique security problems in crypto
- Estimated costs of fraud, account take over, and possible regulatory fines (eg: OFAC Sanctioned entities)
- Graph theory and blockchain analysis problems at scale
- Using Nvidia Rapids, Apache Arrow & Graphistry with Databricks
- Onboarding business teams into Databricks for collaboration

Using ML to improve platform stability and ITOps
- Crypto never sleeps: 24x7 trading
- Cost of an outage
- Forecasting techniques and libraries + tradeoffs (simple regression, prophet, sarimax)
- Integrating non-traditional indicators/features to forecast IT infrastructure and platform behaviors
- Operationalizing predictions for early warning to O11y tools like Grafana & DataDog

In closing: revenue generated and cost savings calculations.

Session Speakers

Anthony Tellez

Head of Machine Learning & AI

BlockFi

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