Top 5 Jupyter Notebook fraud-detection Projects

fraud-detection-handbook

1 429 0.0 Jupyter Notebook

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook
fraud-detection-using-machine-learning

7 248 1.8 Jupyter Notebook

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
MLSys-NYU-2022

9 238 10.0 Jupyter Notebook

Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022

Project mention: Where to start | /r/mlops | 2023-09-13

There are 3 courses that I usually recommend to folks looking to get into MLE/MLOps that already have a technical background. The first is a higher-level look at the MLOps processes, common challenges and solutions, and other important project considerations. It's one of Andrew Ng's courses from Deep Learning AI but you can audit it for free if you don't need the certificate: - Machine Learning in Production For a more hands-on, in-depth tutorial, I'd recommend this course from NYU (free on GitHub), including slides, scripts, full-code homework: - Machine Learning Systems And the title basically says it all, but this is also a really good one: - Hands-on Train and Deploy ML Pau Labarta, who made that last course, actually has a series of good (free) hands-on courses on GitHub. If you're interested in getting started with LLMs (since every company in the world seems to be clamoring for them right now), this course just came out from Pau and Paul Iusztin: - Hands-on LLMs For LLMs I also like this DLAI course (that includes Prompt Engineering too): - Generative AI with LLMs It can also be helpful to start learning how to use MLOps tools and platforms. I'll suggest Comet because I work there and am most familiar with it (and also because it's a great tool). Cloud and DevOps skills are also helpful. Make sure you're comfortable with git. Make sure you're learning how to actually deploy your projects. Good luck! :)

benford_py

1 148 0.0 Jupyter Notebook

Python implementation of Benford's Law tests.
demo-fraud-detection-with-p2p

1 61 5.5 Jupyter Notebook

Exploring Neo4j and Graph Data Science for Fraud Detection

Project mention: demo-fraud-detection-with-p2p: NEW Extended Research - star count:50.0 | /r/algoprojects | 2023-09-27

WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).