Machine Learning Algorithms

A machine learning project to predict wine quality based on physicochemical properties. It includes comparisons of model performance with and without imputation techniques using various algorithms.

Цель проекта - анализ тональности твитов. Для сообщений пользователей из тестового набора, необходимо предсказать с максимально возможным результатом, является ли тональность твита положительной, отрицательной или нейтральной.

A land cover classification task performed with machine learning modelling on Sentinel-2 data for Gibraltar.

Many pregnant women die from pregnancy issues as a result of a lack of information on maternal health care during and after pregnancy. It is more common in rural regions and among lower-middle-class families in emerging countries. During pregnancy, every minute should be observed to ensure the proper growth of the baby and the safe delivery.

the code uses KNN, Gaussian Naive Bayes & SVM to classify images. It preprocesses, normalizes data, applies PCA , computes accuracy, precision etc. It evaluates k-NN using Euclidean distance & cosine similarity, visualizing results with line plots, 3D scatter plots, & confusion matrices to demonstrate classifier performance.

This project showcases a Network Intrusion Detection System (NIDS) designed to bolster cybersecurity defenses against evolving threats

Data Mining | Machine Learning

Combat misinformation and fake news by accurately predicting the truth of the article to prevent the spread of harmful information that could lead to confusion, panic, or societal harm.

Enhance customer satisfaction in the airline industry by identifying dissatisfaction factors and accurately predicting passenger satisfaction to provide actionable insights, refine services, and boost passenger loyalty.

This project consists of Two models that classifies the potability of water .

A Time-Series Machine Learning project aimed at accurate predicting curreny pair exchange rates using ARIMA, SARIMA and LSTM.

Spotify Music Classifier with Machine Learning Using Spotify API

This project on placement prediction integrates machine learning with database management using MySQL for user authentication. The project involves data preprocessing, feature engineering, and the implementation of supervised learning techniques to train the model.

Using various machine learning models (Logistic Regression, Gaussian Naïve Bayes, KNN, Gradient Boosting Classifier, Decision Tree Classifier, Random Forest Classifier.) to predict whether a company will go bankrupt in the following years, based on financial attributes of the company; Addressed the issue of imbalanced classes, different importance

Navie Base Classifier for classifiing imdb comments

The goal of this project is to create a classifier and see how accurately it can predict song genres. Taking a dataset from Spotify [Pandya, 2022], which is al- ready using machine learning algorithms for these purposes, can help assess if the resulting model can be considered apt for a large-scale business.

Develop machine learning models that detect diseases from blood test data. Utilizing machine learning, it analyzes patterns and predicts potential health conditions, offering users early insights for proactive care.

In this study, after detailed Exploratory Data Analysis, 5 different machine learning models were tested on Titanic Data to answer the question "What sorts of people were more likely to survive?" and the best model for survival prediction was determined.