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on
1
Intro
2
Ranjans background
3
Bitcoins history
4
Big Points
5
Product from Attention
6
Credit Card Fraud
7
Social media profiles
8
Flavors of fraud
9
Fraud detection using machine learning
10
Problem formulation
11
Pipeline
12
Models
13
Training Model
14
Fraud is Animating
15
Data skewed
16
Context diagram
17
Visualization
18
Fraud Detection
19
AP Tests
20
Deep Learning
21
Transactions
22
Entity Recognition
23
Audience
24
Question
Description:
Explore fraud detection techniques in Bitcoin payment networks through this 37-minute conference talk by Soups Ranjan from Coinbase. Gain insights into Bitcoin's history, credit card fraud, and social media profiles as they relate to cryptocurrency fraud. Learn about machine learning approaches for fraud detection, including problem formulation, pipeline development, and model training. Discover the challenges of working with skewed data and the importance of context in fraud analysis. Examine visualization techniques, entity recognition, and deep learning applications in transaction monitoring. Engage with the audience Q&A session to further understand the complexities of fraud detection in the cryptocurrency space.

Fraud Detection in Bitcoin Payment Networks

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