abhishekdbihani / Home-Credit-Default-Risk-Recognition
The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.
☆18Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for Home-Credit-Default-Risk-Recognition
- A comprehensive credit risk model and scorecard using data from Lending Club☆135Updated 3 years ago
- ☆21Updated 3 weeks ago
- a collection of different Exploratory Data Analysis Aproaches☆84Updated 4 years ago
- Python Feature Engineering Cookbook Second Edition, published by Packt☆77Updated last year
- Predicting how capable each applicant is of repaying a loan (Kaggle Challenge)☆11Updated last year
- Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discre…☆83Updated 4 years ago
- Modern Time Series Forecasting with Python 2E, Published by Packt☆47Updated last week
- Time Series Analysis with Python Cookbook, Second Edition - Published by Packt☆22Updated last week
- Notebook to walk through Bayesian testing with Kaggle data☆39Updated 3 years ago
- This repository hosts code for my Time Series videos part of playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJ…☆259Updated last year
- credit-risk-modeling☆21Updated 3 years ago
- A simple Jupyter Notebook walking through how to perform time series forecasting with Facebook Prophet.☆81Updated 3 years ago
- Deployment Heroku☆56Updated 5 months ago
- ☆34Updated 3 years ago
- Exploratory Data Analysis with Python Cookbook, published by Packt☆67Updated last year
- Portofolio repository for Udacity Data Scientist Nanodegree☆38Updated 4 years ago
- There are several exploratory data analysis (EDA) analyzes in this file. More data analytics and business approached than machine learnin…☆40Updated 3 years ago
- Files for my Udemy course specifically on Time Series Analysis☆60Updated 3 years ago
- Portfolio in Python☆41Updated last year
- The objective of this project is to analyze the 3 million grocery orders from more than 200,000 Instacart users and predict which previou…☆69Updated 2 years ago
- The goal of this notebook is to implement and compare different approaches to predict item-level sales at different store locations.☆34Updated 2 years ago
- A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python☆136Updated this week
- Solved end-to-end machine learning projects☆30Updated last year
- Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that a…☆43Updated 5 years ago
- Jupyter Notebook from Selenium Tutorial: Scraping Glassdoor.com"☆93Updated last year
- data science interview questions company wise which include the data analyst , junior data scientist , machine learning engineer etc. pos…☆13Updated 2 years ago
- Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt☆187Updated last year
- Machine Learning Engineering with Python☆171Updated last year