Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Learning to create Machine Learning Algorithms

Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied

The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

Final Year Project on Road Accident Prediction using user's Location,weather conditions by applying machine Learning concepts.

A machine learning project that predicts results of a football match

Heart disease prediction using normal models and hybrid random forest linear model (HRFLM)

Detect Fraudulent Credit Card transactions using different Machine Learning models and compare performances

A machine learning web application use to predict chances of heart disease, built with FLASK and deployed on Heroku.

Implementation of a Random Forest classifier in both Python and Scala

This is a Malware Detection ML model made using Random Forest Algorithm

A machine-learning project to determine if a certain mushroom is edible or poisonous.

AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset

In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.

Various Classification models used are Logistic regression, K-NN, Support Vector Machine, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification using Python

The purpose of this project is to be able to automatically and efficiently segment and classify high-grade and low-grade gliomas.

I have used Multinomial Naive Bayes, Random Trees Embedding, Random Forest Regressor, Random Forest Classifier, Multinomial Logistic Regression, Linear Support Vector Classifier, Linear Regression, Extra Tree Regressor, Extra Tree Classifier, Decision Tree Classifier, Binary Logistic Regression and calculated accuracy score, confusion matrix and…

Technic analyzer with ML (RTF) and signal sender bot using telegram

In the banking industry, detecting credit card fraud using machine learning is not just a trend; it is a necessity for banks, as they need to put proactive monitoring and fraud prevention mechanisms in place. Machine learning helps these institutions reduce time-consuming manual reviews, costly chargebacks and fees, and denial of legitimate tran…

Breast Cancer Wisconsin (Diagnostic) Prediction Using Various Architecture, though XgBoost Classifier out performed all