Ozone Day AdaBoostClassifier and Random Forest Tree Classifier with Machine Learning

Classification of grape varieties in Python using Multinomial Logistic Regression, Decision Trees and Random Forests

Implementation of a machine learning algorithm(AGB) based on the research paper.

python Machine learning

FL-HDC: Hyperdimensional Computing Design for the Application of Federated Learning (IEEE AICAS2021)

Artificial Intelligence, Computer Network, Machine Learning, Python, DAA, Distributed System, Internet of Things (IoT), Data Science and Analysis.

A New Classification Method Using Soft Decision-Making Based on an Aggregation Operator of Fuzzy Parameterized Fuzzy Soft Matrices

The main repository for the project "Analysis of the load structure of the consumer".

Application of machine learning in Python | Coursera

This is my attempt for the #AndroidDevChallenge

Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.

This repository contains model files that can be used to predict stock and insurance churns using machine learning algorithms.

Final project progress will be posted here.

Splitting the advertising data (advertising.csv) into training and testing data sets, then choosing and training a classification machine learning algorithm; Getting the accuracy of the ML model; Using feature engineering skills to create new features and improve my ML model;

Files for Feature Engg, Feature Scaling, Feature Selection, Statistics and Implementation of every Machine Learning Algorithm.

A simple Machine Learning algorithm that calculates the price of houses based on weighted attributes and a large training dataset.