This project is an image classification project using a deep-learning based on Convolutional Neural Networks (CNNs) with Keras. The Dogs vs. Cats is a classic problem for anyone who wants to dive deeper into deep-learning.

Graphs, plots and maps made using python.

Better multi-class confusion matrix plots for Scikit-Learn, incorporating per-class and overall evaluation measures.

Classification Models for Practice

R scripts for RF and RBF-SVM for Acute Myeloid Leukemia subtypes multiclass classification using gene expression profiles. LASSO feature selection, SMOTE sampling, 10-fold cross-validation, variable importance plot, PCA plot, normalized Confusion Matrix, GSE13159.

Streamlit application to predict risk of cardiovascular disease

An LSTM model to label articles into 5 categories.

ML_Logistic_Regression

Objective: Build a CNN classifier that will be able to accurately predict the species of plant seedling based on an image of that seedling taken from the top.

This research work summarized different machine learning algorithms to create models for predicting diabetes patients utilizing the Diabetes Dataset (PIDD) from the UCI repository. The classifiers were K-Nearest Neighbors, Naïve Bayes, Support Vector, Decision Tree, Random Forest, Logistic Regression and Ensemble Model using a voting classifier.

Fraud Detection in Mobile Money Transactions using Machine Learning . A binary classification project comparing six models (Logistic Regression, Naive Bayes, Decision Tree, Random Forest, KNN, SVM) on the PaySim dataset. Includes data preprocessing, class balancing, feature importance analysis, and model evaluation (accuracy, precision, recall, F1-

The aim of this project is to predict whether a credit card transaction is fraudulent or not, based on the transaction amount, time and other transaction related data.It aims to track down credit card transaction data, which is done by detecting anomalies in the transaction data.

This repository contains a Convolutional Neural Network which classifies whether a person is suffering from COVID-19 or not with the help of Chest X-rays.

The displayed project constitutes a Placement_prediction_model. Which can be used to predict the Probability of getting hired for a job with an accuracy of 83% on testing data. This model comprises of an ensemble of decision tree classifiers.

Deep learning application for term deposit prediction on imbalanced dataset

This project analyzes historical weather data to identify patterns and predict future weather conditions, focusing on extreme events and temperature trends across Europe.

Supervised Machine Learning project to predict airline passenger satisfaction using Python and sklearn. Includes model training, evaluation, and deployment using Gradio for interactive prediction. Visualizations created with Matplotlib and Seaborn to support data-driven insights.

Exploration of model performance, bias-variance tradeoffs, and dataset effects on classification accuracy with fully reproducible simulated data. This project was done in Python.

In simple, a Loan (borrowing money from a bank) is the sum of money that you borrow from the bank or lending financial institution in order to meet needs. These needs could result from planned or unplanned events, and by borrowing, you incur a debt that you have to pay within the agreed duration on your contract.