Principal_Component_Analysis

Tensorflow 2.0 and Keras Regression and Classification including TensorBoard.

A machine learning project which predicts the healthcare based on given certain features.

This repository contains a pre-trained image classification model utilizing the VGG16, VGG19 and EfficientNet-B7 architecture. The model supports transfer learning and fine-tuning, offering flexibility for adapting to specific image recognition tasks.

Breast cancer classifier using Logistic regression, SVC, K-NN, and Random Forest Classification

Development and testing of various models for classification of Breast Cancer and Cancer Recurrence from human extracellular RNA transcripts. Final Project for CSE 283: Data Wrangling in Bioinformatics

Classification of Breast Cancer diagnosis Using Support Vector Machines

Small project to accurately predict nature of a tumour (benign/malignant) using the UCI Wisconsin breast cancer dataset (https://www.kaggle.com/uciml/breast-cancer-wisconsin-data)

Breast cancer detection using machine learning with deployment of model

Unsupervised clustering of transcriptomic and proteomic data for breast cancer patients

Breast Cancer Classification ( SVM Implementation)

Breast cancer detection using machine learning classification is a project where you build a model to identify whether a given set of medical features indicates the presence of breast cancer. This project involves using a labeled dataset of medical records, where each record is classified as either indicating breast cancer or not.

Project on Neural Networks for Nanoparticle Breast Cell Classification - Machine Learning (MEng), supervised by Prof. C. Sansone and Eng. M. Gravina(2024)

In this project we will built Support Vector Machine (SVM) and K-Nearest-Neighbors Classification model using uci breast cancer data repository.

Logistic Regression Model has been used to predict the chances of Breast Cancer

Developing an advanced Breast Cancer Classification system using state-of-the-art Deep Learning techniques. This project aims to enhance early detection by analyzing Fine needle aspiration is a type of biopsy procedure's dataset, leveraging neural networks (NNs) and other deep learning architectures.

Analysis of RNA-Seq data for approximately 3500 breast tumors from the SCAN-B project to investigate differential splicing patterns between molecular subtypes and clinical phenotypes

This is about to check the category of breast cancer either M type or B type.