dachosen1 / Feature-Engineering-for-Fraud-Detection

Related projects ⓘ

Alternatives and complementary repositories for Feature-Engineering-for-Fraud-Detection

• saritmaitra / Segmentation-Clustering
  Recency, Frequency, and Monetary are three behavioral attributes and are quite simple, in that they can be easily computed for any databa…
  ☆15Updated last year
• anurag-code / Survival-Analysis-Intuition-Implementation-in-Python
  Quick Implementation in python
  ☆53Updated 4 years ago
• jimmycy93 / Credit-Card-Fraud-Detection
  A project on machine learning techniques dealing with imbalanced classification (Python)
  ☆10Updated 7 years ago
• Apress / beginning-anomaly-detection-using-python-based-dl
  Source Code for 'Beginning Anomaly Detection Using Python-Based Deep Learning' by Sridhar Alla and Suman Kalyan Adari
  ☆82Updated 5 years ago
• chudzikr / Fraud_Detection_in_Python
  Fraud Detection in Python, DataCamp course
  ☆12Updated 5 years ago
• adib0073 / Time_Series_Anomaly_Detection
  Effective Approaches for Time Series Anomaly Detection
  ☆11Updated 4 years ago
• AntonsRuberts / datascience_marketing
  Here I'll publish all of my personal projects that relate to Data Science in Marketing
  ☆43Updated 4 years ago
• DiegoUsaiUK / Propensity_Modelling
  Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
  ☆28Updated last year
• baumanab / udacity_ABTesting
  Project work for Udacity's AB Testing Course
  ☆81Updated 7 years ago
• logicalclocks / aml_end_to_end
  AML End to End Example
  ☆52Updated 2 years ago
• MaartenGr / CustomerSegmentation
  Analysis for Customer Segmentation
  ☆65Updated 4 years ago
• jalajthanaki / Customer_lifetime_value_analysis
  Customer life time analysis (CLV analysis). We are using Gamma-Gamma model to estimate average transaction value for each customer.
  ☆45Updated 6 years ago
• mscharth / forecasting
  Forecasting lectures and tutorials using Python
  ☆100Updated 7 years ago
• MaartenGr / feature-engineering
  Tips for Advanced Feature Engineering
  ☆52Updated 4 years ago
• bibtissam / LSTM-Attention-FraudDetection
  Enhanced Credit Card Fraud Detection based on Attention mechanism and LSTM deep Model
  ☆38Updated 2 years ago
• carlomazzaferro / scikit-hts-examples
  Example usage of scikit-hts
  ☆56Updated 2 years ago
• druce / iowa
  Iowa House Prices Kaggle (top 5%)
  ☆13Updated 4 months ago
• exploripy / exploripy
  Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.
  ☆50Updated last year
• solegalli / Python-Feature-Engineering-Cookbook-First-Edition
  ☆30Updated 5 months ago
• waittim / graph-fraud-detection
  Colab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend.
  ☆31Updated 3 years ago
• solegalli / machine-learning-imbalanced-data
  Code repository for the online course Machine Learning with Imbalanced Data
  ☆161Updated 2 months ago
• yoonhwang / hands-on-data-science-for-marketing
  ☆26Updated 3 years ago
• bodywork-ml / ml-pipeline-engineering
  Best practices for engineering ML pipelines.
  ☆37Updated 2 years ago
• AidanCooper / shap-analysis-guide
  How to Interpret SHAP Analyses: A Non-Technical Guide
  ☆45Updated 3 years ago
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆88Updated 10 months ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆45Updated 3 years ago
• elena-roff / price-modeling-rf
  Data Analysis and Machine Learning with Python: EDA with ECDF and Correlation analysis, Preprocessing and Feature engineering, L1 (Lasso)…
  ☆31Updated 7 years ago
• smazzanti / tds_black_box_models_more_explainable
  Jupyter Notebook used for writing the article "Black-Box models are actually more explainable than a Logistic Regression" published in To…
  ☆72Updated last year
• KishManani / m5-forecasting-tutorial
  An end-to-end tutorial to forecast the M5 dataset using feature engineering pipelines and gradient boosting.
  ☆14Updated last year
• alteryx / predict-household-poverty
  Predict the poverty of households in Costa Rica using automated feature engineering.
  ☆23Updated 4 years ago