curiousily / Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
☆531Updated 5 years ago
Alternatives and similar repositories for Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras:
Users that are interested in Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras are comparing it to the libraries listed below
- Credit card fraud detection through logistic regression, k-means, and deep learning.☆221Updated 6 years ago
- Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook☆101Updated 2 years ago
- ☆113Updated 7 years ago
- A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the differ…☆121Updated 7 years ago
- ☆6Updated 3 years ago
- To design a predictive model using xgboost and voting ensembling techniques and extract insights from the data using pandas, seaborn and …☆39Updated 6 years ago
- Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to …☆133Updated 6 years ago
- Enhanced Credit Card Fraud Detection based on Attention mechanism and LSTM deep Model☆40Updated 2 years ago
- Machine learning models to automatically predict credit card frauds☆11Updated 6 years ago
- Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Fraud…☆75Updated 5 years ago
- Anomaly detection algorithm implementation in Python☆130Updated 4 years ago
- An LSTM Autoencoder for rare event classification☆108Updated 5 years ago
- Anomaly detection implemented in Keras☆374Updated 6 years ago
- Lending Club Loan data analysis☆160Updated 5 years ago
- Anomaly detection for temporal data using LSTMs☆223Updated 3 years ago
- This repo contains my jupyter notebook for a data challenge for building a machine learning model to identify fraud in e-commerce transac…☆12Updated 7 years ago
- This project shows how to perform customers segmentation using Machine Learning algorithms. Three techniques will be presented and compar…☆9Updated 4 years ago
- In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays an…☆99Updated 6 years ago
- AI deep learning neural network for anomaly detection using Python, Keras and TensorFlow☆198Updated 4 years ago
- ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xg…☆271Updated 4 years ago
- experiments with python☆378Updated 7 years ago
- testing scikit-learn Isolation Forest☆76Updated 6 years ago
- Machine learning model for Credit Card fraud detection☆92Updated 4 years ago
- Anomaly detection for streaming data using autoencoders☆192Updated 2 years ago
- Customer segmentation using k-means clustering in python☆57Updated 6 years ago
- Tuning XGBoost hyper-parameters with Simulated Annealing☆52Updated 7 years ago
- This is an experimental of anomalies detection by applying different approach to the problem. PCA component regularization method, K-Mean…☆21Updated 5 years ago
- ☆137Updated 6 years ago
- ☆169Updated 2 years ago
- Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".☆574Updated 2 years ago