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

DSLR (Datascience X Logistic Regression) : a multi class logistic regression model that sorts Hogwarts students to their houses.

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

The notebook contains Python code for various machine learning tasks and models. Here is an overview of its content:

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.

research aimed at predicting outcomes such as: post-operation mortality, Impact of comorbidities on ICU admission after cardiac surgeries, total icu stay post emergency operation, as well as utilizing deep learning to perform CT/MRI segmentation.

Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female

This project includes Twitter Social Media Analytics, Facebook Graph Analysis and News API Data Analysis. See the final report for full understanding.

This project includes both Diabetes Prediction using Machine Learning Algorithms and Graph Analysis using Neo4j. Have a look at the Report for complete understanding.