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advanced-house-price-prediction-

data-preprocessing-project-template

This repository provides a comprehensive template for data preprocessing tasks essential for machine learning projects. The template follows a structured approach to ensure data quality and readiness for model building. It covers various aspects of data preprocessing

decision-tree-regression

This repository contains a project that applies Decision Tree Regression to analyze and predict the salaries of employees based on their position levels. The project utilizes Python and its data science libraries to build a predictive model that estimates employee salaries based on their position and level.

facial-emotion-detection

Developed and deployed an end-to-end face recognition and facial emotion detection system using advanced machine learning and deep learning techniques. Implemented real-time image and video processing with OpenCV and utilized Convolutional Neural Networks (CNN) in TensorFlow and Keras for emotion classification.

linear-regression

Linear Regression on Salary Data This repository contains a project that applies linear regression to analyze and predict the salary of employees in a multinational corporation (MNC). The project leverages Python and its data science libraries to build a predictive model that estimates employee salaries based on various features.

multiple-linear-regression

This repository is a project that applies multiple regression to analyze and predict the profit of startups based on various factors. The project utilizes Python and its data science libraries to build a predictive model that estimates startup profits based on features such as R&D Spend, Administration Spend, Marketing Spend, State.

peopledb

This project is a comprehensive Employee Database Management System built using Java and SQL, with DBeaver serving as the database management tool. The system facilitates efficient storage, retrieval, and management of employee data within an organization.

polynomial-regression

random-forest-regression

This repository contains a project that applies Random Forest Regression to analyze and predict the salaries of employees based on their position levels. The project utilizes Python and its data science libraries to build a predictive model that estimates employee salaries based on their position and level.

resume-ats-scanner-project-

ATS Scanner for Resumes using Data Analytics in Jupyter Notebook to optimize resumes. Key features: resume parsing, keyword matching, scoring system, and data visualization. Technologies: Python, pandas, numpy, NLTK, Spacy, matplotlib, seaborn, regex, scikit-learn. Empowering job seekers with actionable insights.

support-vector-regression

Support Vector Regression - This repository contains a project that applies Support Vector Regression (SVR) to analyze and predict the salaries of employees based on their position levels. The project utilizes Python and its data science libraries to build a predictive model that estimates employee salaries based on their position and level.