Build and evaluate several machine learning algorithms to predict credit risk.
-
Updated
Oct 12, 2022 - Jupyter Notebook
Build and evaluate several machine learning algorithms to predict credit risk.
Supervised Machine Learning and Credit Risk
Evaluate the performance of multiple machine learning models using sampling and ensemble techniques and making a recommendation on whether they should be used to predict credit risk.
Insurance claim fraud detection using machine learning algorithms.
This is a very Important part of Data Science Case Study because Detecting Frauds and Analyzing their Behaviours and finding reasons behind them is one of the prime responsibilities of a Data Scientist. This is the Branch which comes under Anamoly Detection.
Using Supervised Machine Learning algorithms to identify credit risks
Six different techniques are employed to train and evaluate models with unbalanced classes. Algorithms are used to predict credit risk. Performance of these different models is compared and recommendations are suggested based on results.
For this analysis, we used computational linguistics and biometrics to systematically identify the trend using various news articles and closing prices using the "CoinGecko CSV & Crypto News API"!
Supervised Machine Learning and Credit Risk
Uses several machine learning models to predict credit risk.
Build and evaluate several machine learning algorithms to predict credit risk
Resampling exercise to predict accuracy, precision, and sensitivity in credit-loan risk
Extract data provided by lending club, and transform it to be useable by predictive models.
Testing 6 different machine learning models to determine which is best at predicting credit risk.
Analysis of different machine learning models' performance on predicting credit default
Using machine learning to train and evaluate models with unbalanced classes to determine the best models to predict credit risk.
Train and test multiple Machine Learning models to predict risk based on consumer credit profiles.
Built and evaluated variety of supervised machine learning algorithms to predict credit risk.
using machine learning to assess credit risk
Add a description, image, and links to the balanced-random-forest topic page so that developers can more easily learn about it.
To associate your repository with the balanced-random-forest topic, visit your repo's landing page and select "manage topics."