A machine learning model after detailed image processing applications that classifies a bee as either honey bee or bumble bee

Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository

Python project for Banknotes Analysis.

Titanic Survivor Analysis and Prediction

Contains nongraded challenge during FTDS Batch 001-Phase 1 at Hacktiv8

Built machine learning algorithms (Decision Tree Classifier, Random Forest Classifier & Support Vector Classifier) to best predict the credit card approval.

Face Recognition with SVM, starting from basics

This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.

Real or Fake Job Prediction classifier

In this data analysis project, I will explore the application of Principal Component Analysis (PCA) to reduce the dimensionality of a dataset and enhance the performance of a machine learning model.

Identification of the Employees who are most likely to switch the jobs for package negotiations & Job offerings. Also, Analyzing the particular departments where the attrition rate is high and to take the preventive measures by using Decision Tree Classifer, Random Forest Classifier, Support Vector Classifier, Logistic Regression, K Nearest Neig…

This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification. The goal is to train an SVM classifier to predict whether a user will purchase a particular product or not.

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Breast Cancer Prediction

This is about how to make Diabetes Prediction with Machine Learning. We are developing a machine learning model capable of predicting whether someone may have diabetes based on health data and specific parameters. Using the right machine learning algorithms, we will process this data to provide valuable predictions for patients and medical

The objective of this project is to showcase the use of Machine Learning models to answer the question of loan default prediction based on certain parameters from the German bank dataset.

The sinking of the RMS Titanic is one of the most infamous shipwrecks in world history. In this model, need to analyse what sorts of people were likely to survive. We also need to apply the tools of machine learning to predict which passengers survived in this tragedy.

To create a system that effectively detects and prevents credit card fraud using machine learning techniques, ensuring the security of financial transactions and protecting customers from fraudulent activities.

Machine learning library for classification tasks