pwinslow / Fraud-DetectionLinks
This repo contains my jupyter notebook for a data challenge for building a machine learning model to identify fraud in e-commerce transaction data
☆13Updated 8 years ago
Alternatives and similar repositories for Fraud-Detection
Users that are interested in Fraud-Detection are comparing it to the libraries listed below
Sorting:
- Credit card fraud detection through logistic regression, k-means, and deep learning.☆244Updated 7 years ago
- Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook☆104Updated 2 years ago
- Customer segmentation using k-means clustering in python☆59Updated 7 years ago
- Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso…☆91Updated last year
- 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
- iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transaction…☆560Updated 6 years ago
- Different clustering approaches applied on different problemsets☆40Updated 5 years ago
- Lending Club Loan data analysis☆167Updated 6 years ago
- Predict seasonal item sales using classical time-series forecasting methods like Seasonal ARIMA and Triple Exponential Smoothing and curr…☆31Updated 5 years ago
- Improve marketing campaign of a Portuguese bank by analyzing their past marketing campaign data and recommending which customer to target☆61Updated 7 years ago
- Time Series Decomposition techniques and random forest algorithm on sales data☆62Updated 3 years ago
- In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays an…☆111Updated 7 years ago
- Credit Risk analysis by using Python and ML☆164Updated 7 years ago
- Methods with examples for Feature Selection during Pre-processing in Machine Learning.☆363Updated 5 years ago
- 📈Forecasting Total amount of Products using time-series dataset consisting of daily sales data provided by one of the largest Russian so…☆57Updated 5 years ago
- Developed a supervised machine learning system that can estimate a country's GDP per capita using regression algorithms.☆31Updated last year
- Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast eva…☆326Updated 6 years ago
- This repository contains a throughout explanation on how to create different deep learning models in Keras for multivariate (tabular) tim…☆139Updated 6 years ago
- testing scikit-learn Isolation Forest☆77Updated 7 years ago
- Various projects in Linear Regression, Logistic Regression, k Nearest Neighbors, Decision Trees, Random Forests, SVM☆141Updated 2 years ago
- In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calcul…☆218Updated 2 years ago
- This portfolio is a compilation of notebooks which I created for Data Science related tasks like Tutorials, Exploratory Data Analysis, an…☆82Updated 7 months ago
- Data Analysis and Machine Learning with Python: EDA with ECDF and Correlation analysis, Preprocessing and Feature engineering, L1 (Lasso)…☆33Updated 8 years ago
- Understand why employees leave a company and apply various machine learning models to predict the next leaver!☆53Updated 7 years ago
- ☆220Updated 3 years ago
- A comprehensive credit risk model and scorecard using data from Lending Club☆144Updated 4 years ago
- Predicting how capable each applicant is of repaying a loan (Kaggle Challenge)☆12Updated 2 years ago
- Exploratory data analysis 📊using python 🐍of used car 🚘 database taken from ⓚ𝖆𝖌𝖌𝖑𝖊☆227Updated 6 years ago
- Genpact ML hackathon 2018 hosted on Analytics Vidhya. Food demand forecasting - 79th rank solution☆11Updated 6 years ago
- Reproducible machine learning notes in Python and R to record my learning journey in Data Science☆18Updated 6 years ago