Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle

Last update: Feb 04, 2022

Overview

CSCD 429 Project

The following repository contains the project of Team 6.

Team Members

Blake Chalpin (b-chalpin)
Harjasleen Gill (hgill17)
Jacob Watkins (colmendean123)
Sean Zahller (SeanZahller)

Description

Credit card fraud detection.

We used the credit card fraud dataset from Kaggle.

Installation

Using Conda

To create the virtual environment and install required Python packages, run the following commands in the terminal:

conda env create -f environment.yml
conda activate cscd429-team6-project

Without Conda

If you do not have Conda installed, the packages may still be installed using the following command:

pip install -r requirements.txt

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

Owner

Sean Zahller

Eastern Washington University BCS. Projects listed in resume are located in the Stars section of my profile.

GitHub Repository

MLOps pipeline project using Amazon SageMaker Pipelines

This project shows steps to build an end to end MLOps architecture that covers data prep, model training, realtime and batch inference, build model registry, track lineage of artifacts and model drif

3 Sep 16, 2022

Machine Learning from Scratch

Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin

0 Jul 05, 2022

Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared

Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset

5 Apr 21, 2022

cleanlab is the data-centric ML ops package for machine learning with noisy labels.

cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear

51 Nov 28, 2022

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

8.4k Dec 30, 2022

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.

3 Apr 03, 2022

Extreme Learning Machine implementation in Python

Python-ELM v0.3 --- ARCHIVED March 2021 --- This is an implementation of the Extreme Learning Machine [1][2] in Python, based on scikit-learn. From

511 Dec 20, 2022

moDel Agnostic Language for Exploration and eXplanation

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

1.2k Jan 04, 2023

Made in collaboration with Chris George for Art + ML Spring 2019.

Deepdream Eyes Made in collaboration with Chris George for Art + ML Spring 2019.

1 Jan 12, 2022

database for artificial intelligence/machine learning data

AIDB v0.0.1 database for artificial intelligence/machine learning data Overview aidb is a database designed for large dataset for machine learning pro

1 Oct 24, 2021

Simple and flexible ML workflow engine.

This is a simple and flexible ML workflow engine. It helps to orchestrate events across a set of microservices and create executable flow to handle requests. Engine is designed to be configurable wit

295 Jan 06, 2023

Automatic extraction of relevant features from time series:

tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis

7k Jan 06, 2023

An easier way to build neural search on the cloud

Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the effici

17k Jan 01, 2023

Provide an input CSV and a target field to predict, generate a model + code to run it.

automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn

1.8k Jan 04, 2023

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

1.6k Dec 31, 2022

A single Python file with some tools for visualizing machine learning in the terminal.

Machine Learning Visualization Tools A single Python file with some tools for visualizing machine learning in the terminal. This demo is composed of t

35 Dec 29, 2022

A simple machine learning package to cluster keywords in higher-level groups.

Simple Keyword Clusterer A simple machine learning package to cluster keywords in higher-level groups. Example: "Senior Frontend Engineer" -- "Fronte

10 Dec 18, 2022

To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

1 Jan 11, 2022

A Pythonic framework for threat modeling

pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In

644 Dec 20, 2022

Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale.

Model Search Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers sp

1 Dec 13, 2021