heart disease detection using different ML algorithms Like SVM ,KNN, Ensemble method ,decision tree,LR

Predicting the churn of telecommunication custumers

Self Project

Using Supervised Machine Learning to predict the success of a Falcon 9 landing.- DataScience

The online payment fraud analysis project follows several step approach from data preprocessing through model evaluation, result comparison and final model selection, using transaction patterns to identify fraud indicators including account draining, suspicious transfers, and balance inconsistencies.

In this project I intend to predict customer churn on bank data.

Natural language processing on tweets

Machine Learning Algorithms Scratch Implementations

Azure ML Pipeline Project, completed for Nanodegree

Implementations of linear regression, logistic regression and perceptron using gradient descent. A implementation of Leave-one-out cross evaluation is also included in the logistic and perceptron files.

This is a binary classification problem. There are numerous factors that can contribute to the presence of heart disease. What is the most important factor causing heart disease? Can an accurate classifier be built to predict the presence of heart disease in patients? These are the questions we want to answer with this project.

This model predicts the winning probabilities for both teams during the second innings of an IPL match.

This is Date Fruit Data taken from Kaggle. This data severs a classification problem to solved. Using various features of the fruit classify the fruit to its type.

Group project for the course BUDT737: Enterprise Cloud Computing and Big Data

Language Detector Loads and cleans text data, trains a language classification model using TF-IDF and Logistic Regression, evaluates it, and enables interactive language prediction with saved model reuse.

A sentiment analysis project on Twitter tweets using Python for text preprocessing and visualization. The project includes Exploratory Data Analysis (EDA) and sentiment classification using Logistic Regression and Random Forest models.

SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier

A Classification Model relies on Logistic Regression and Decision Tree Algorithm Has been build in this project to predict severity of Damage based on Earthquake Grade 0-5

Create a model to predict if a customer will leave the bank.

In this repo we're diving into NBA game data to explore the phenomenon of home court advantage.