Analyze the data of ABC consulting company, build a predictive model based on the parameters like age, salary, work experience and predict the preferred mode of transport.
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Updated
Jun 30, 2024 - Jupyter Notebook
Analyze the data of ABC consulting company, build a predictive model based on the parameters like age, salary, work experience and predict the preferred mode of transport.
Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.
A Machine Learning project for Cardiovascular disease prediction
This project is dedicated to accurately classify Alzheimer's disease into Demented, Non-demented and Converted Category.
Model for easy facilitation of visa processing and approvals
Advancing Cybersecurity with AI: This project fortifies phishing defense using cutting-edge models, trained on a diverse dataset of 737,000 URLs. It was the final project for the AI for Cybersecurity course in my Master's at uOttawa in 2023.
Using classical machine learning techniques for classifying the data into 9 classes which can be further used for cancer detection.
This project focuses on predicting the likelihood of diabetes in individuals using ensemble machine learning models. It combines various ensemble techniques, including Random Forest, AdaBoost, Gradient Boosting, Bagging, Extra Trees, XGBoost, Voting Classifier and some others to get predictions.
Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
Prediction-of-House-Grade-Classification using python ( Jupyter Notebook)
Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
This project presents a ML based solution using Ensemble methods to predict which visa applications will be approved and thus recommend a suitable profile for applicants whose visa have a high chance of approval
Detecting and Identifying Fraudulent credit card transactions from normal transactions.
This is just a theoretical Machine Learning Model that will analyze the data and determine where the stroke can occur.
This repository includes the implementation of stacking individual ML models Random forests as an ensemble techniques.
Android malware detection using machine learning.
This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"
The Office of Foreign Labor Certification is facing a dramatic increase in work visa applications, but is hampered by a sluggish review system. It needs to improve the process by developing a way to quickly, accurately identify applications likely to be accepted or rejected so their processing may be prioritized.
A web application to predicted whether a URL/Website is phishing or not by extracting its lexical features.
AS-DMF framework guide
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