Detects Anemia from the analysis of pixels of RBCs using machine learning

Binary Classification for detecting intrusion network attacks. In order, to emphasize how a network packet with certain features may have the potentials to become a serious threat to the network.

To build a predictive model using machine learning to predict the probability of a device failure. When building this model, be sure to minimize false positives and false negatives. The column you are trying to Predict is called failure with binary value 0 for non-failure and 1 for failure.

Lab Assignments of Course Web Mining (CSE-3024)

Predicting wine quality scores based on sensory data using machine learning models in Python

This repository contains various case studies I did using machine learning techniques and python libraries. Also this repository contains the datasets I used

Data Science project that uses popular machine learning techniques to perform HR analytics. The dataset contains employee information from IBM and is linked in the readme.

Made to classify the different species of the Iris flower🌼

A.Nezamisafa

The primary objective is to deploy a robust classifier model that accurately predicts user recommendations, empowering airlines to strategize effectively, understand user behavior, optimize services, and align business strategies with financial objectives.

A repository with our team's final Python project in MGMT 590 Analyzing Unstructured Data course at Krannert School of Management, Purdue University.

Compilación de trabajos realizados en la asignatura de Machine Learning con Python

Uber_fare_prediction. This model based on machine learning. This model predicts 89% accuracy.

🌳 Implements a Filter Tree Classifier for WEKA

OpenCV Machine Learning samples

This repository contains a data science project that focuses on predicting the survival of passengers aboard the Titanic during the tragic disaster. The goal is to build a machine learning model that can accurately predict whether a passenger survived or not based on various features such as socio-economic status, age, gender, and more.

The Community Benefit Insight web site is the first tool to provide data to the public on non-profit hospital community benefit spending. Traditionally, these activities have included free and reduced-cost care, health screenings, and health education