curiousily / Credit-Card-Fraud-Detection-using-Autoencoders-in-KerasLinks
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
☆569Updated 6 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
Sorting:
- Credit card fraud detection through logistic regression, k-means, and deep learning.☆256Updated 7 years ago
- Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook☆105Updated 2 years ago
- ☆113Updated 7 years ago
- Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Fraud…☆84Updated 6 years ago
- A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the differ…☆123Updated 8 years ago
- Lending Club Loan data analysis☆167Updated 6 years ago
- Source Code for 'Beginning Anomaly Detection Using Python-Based Deep Learning' by Sridhar Alla and Suman Kalyan Adari☆84Updated 5 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…☆13Updated 8 years ago
- Various projects in Linear Regression, Logistic Regression, k Nearest Neighbors, Decision Trees, Random Forests, SVM☆140Updated 2 years ago
- In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays an…☆113Updated 7 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 …☆135Updated 7 years ago
- Methods with examples for Feature Selection during Pre-processing in Machine Learning.☆362Updated 5 years ago
- Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso…☆94Updated last year
- ☆220Updated 3 years ago
- Customer segmentation using k-means clustering in python☆59Updated 7 years ago
- An LSTM Autoencoder for rare event classification☆106Updated 5 years ago
- testing scikit-learn Isolation Forest☆77Updated 7 years ago
- Fraud Detection model build with Python (numpy, scipy, pandas, scikit-learn), based on anonymized credit card transactions. The dataset i…☆60Updated 3 years ago
- Different clustering approaches applied on different problemsets☆40Updated 5 years ago
- Machine Learning Experiments and Work☆654Updated 2 years ago
- Data Wrangling, EDA, Feature Engineering, Model Selection, Regression, Binary and Multi-class Classification (Python, scikit-learn)☆273Updated last year
- ☆26Updated 7 years ago
- ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xg…☆282Updated 4 years ago
- Anomaly detection algorithm implementation in Python☆129Updated 5 years ago
- Anomaly detection implemented in Keras☆376Updated 7 years ago
- To design a predictive model using xgboost and voting ensembling techniques and extract insights from the data using pandas, seaborn and …☆47Updated 7 years ago
- Demand Forecasting Models for Kaggle competition☆85Updated 7 years ago
- Time Series Decomposition techniques and random forest algorithm on sales data☆62Updated 3 years ago
- Tuning XGBoost hyper-parameters with Simulated Annealing☆53Updated 8 years ago
- Deep Learning examples with Keras.☆303Updated 2 years ago