RANDEEP RAJ K
randeepraj2003
AI & Data Science enthusiast | ML, Data Analysis & Engineering | Python, SQL, ML/DL | Building data-driven solutions.
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An AI-powered Resume Classification System that automatically categorizes resumes into different job roles using Natural Language Processing (NLP) and Machine Learning.
End-to-end recommendation system project using machine learning techniques, including data preprocessing, exploratory data analysis, model building, and evaluation for personalized recommendations.
Federated machine learning approach for heart disease prediction with privacy-preserving data collaboration.
This repository contains a variety of Data Science projects developed for learning and practical applications. It includes end-to-end workflows such as data preprocessing, EDA, visualization, machine learning model development, evaluation, and deployment-ready code. Each project is structured for clarity and reproducibility.
A simple rule-based chatbot built using Python and NLTK that demonstrates fundamental NLP techniques such as tokenization, lemmatization, cosine similarity, and response generation.
Repositories
7An AI-powered Resume Classification System that automatically categorizes resumes into different job roles using Natural Language Processing (NLP) and Machine Learning.
End-to-end recommendation system project using machine learning techniques, including data preprocessing, exploratory data analysis, model building, and evaluation for personalized recommendations.
No description provided.
Federated machine learning approach for heart disease prediction with privacy-preserving data collaboration.
This repository contains a variety of Data Science projects developed for learning and practical applications. It includes end-to-end workflows such as data preprocessing, EDA, visualization, machine learning model development, evaluation, and deployment-ready code. Each project is structured for clarity and reproducibility.
A simple rule-based chatbot built using Python and NLTK that demonstrates fundamental NLP techniques such as tokenization, lemmatization, cosine similarity, and response generation.
No description provided.