DSLR (Datascience X Logistic Regression) : a multi class logistic regression model that sorts Hogwarts students to their houses.
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Updated
Jun 9, 2024 - Python
DSLR (Datascience X Logistic Regression) : a multi class logistic regression model that sorts Hogwarts students to their houses.
IoT based Novel Approach for Remote Patient Pulse Rate Monitoring System with Stroke Prediction using Logistic Regression
An in-depth exploration of logistic regression models, including data cleaning, model building, and performance evaluation on various datasets.
The notebook contains Python code for various machine learning tasks and models. Here is an overview of its content:
HealthAnalytics-SAS: Leveraging SAS Programming to Uncover Health Trends, Correlations, and Predictive Insights from Comprehensive Health Data Analysis.
Exploring disparities in the COMPAS algorithm: an analysis of recidivism predictions among demographic groups.
Develop a model to predict which retail customers will respond to a marketing campaign. Logistic Regression shows the best performance.
Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.
Machine Learning Algorithms
Classifying Criminal Offenses: Classification Application in Python Using scikit-learn
Predicting which customers are at high risk of leaving your company or canceling a subscription to a service, based on their behavior with your product.
Credit Scoring Project: Perform a Weight of Evidence Logistic Regression Modelling (WoELR) to generate credit scorecard for loan approval.
HR Employee Retention using Logistic Regression
This repository is a related to all about Machine Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python), Feature Selection technique in python etc. Follow Coursesteach for more content
This repository contains classification model for insurance claim
Bank card fraud detection using machine learning. Web application using Streamlit framework
A predictor of GPCR couplings with G-proteins/B-arrs using Transformers
This project analyzes tumor cell data from 550 patients using Python. It involves data cleaning, exploratory analysis, feature engineering, and machine learning to classify tumors as malignant or benign. Techniques include PCA, logistic regression, and k-fold cross-validation to ensure model accuracy and reliability.
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