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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.
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.
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.
This project uses machine learning algorithms (Random Forest Classifier and Decision Tree) to predict student placement likelihood based on age, gender, CGPA, internships, and backlogs. It provides actionable employability insights, aiding career planning. A user-friendly Flask web app will be deployed on Render for broad accessibility.
Precision Tree Module for precision decision analysis, supporting custom nodes (Decision, Chance, and Payoff) with visualization and optimal path calculation.
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.