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Dipesh Joshi's Projects

document-classification-system- icon document-classification-system-

This is a simple AI based document classification system made using Multinomial Naive-Bayes algorithm. This system can classify pdf files to either AI related file or Web related file.

face-recognition-system icon face-recognition-system

This is a face recognition system developed using python which can recognize the face of people whose images are already trained. For the system we have used a pre trained model of 6 hollywood celebrities.

knowlege-graph icon knowlege-graph

This is a small project to build knowledge graph from the text scrapped from articles published in "The Himalayan Times" website on the date 8/11/2023 .Beautifulsoup was used for scraping , Spacy for NLP processings,directed graph was built using networkx.

resume_ranking_and_certificate_verification_system icon resume_ranking_and_certificate_verification_system

This is a Resume Ranking and Certificate Verification System, which uses natural language processing techniques to rank resumes and verify certificates included in them. It compares job descriptions to resumes and ranks them based on their relevance to the job posting. It also verifies certificates through offline and online verification methods.

simple-etl-project-using-airflow icon simple-etl-project-using-airflow

This repository contains the source code and configurations for an Extract, Transform, Load (ETL) project implemented using Apache Airflow. The project focuses on extracting data from various file formats (CSV, TSV, fixed-width), applying basic transformations, and loading the processed data into another CSV file.

udacity-data-engineering-projects icon udacity-data-engineering-projects

Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.

youtube-data-etl-project-using-apache-airflow icon youtube-data-etl-project-using-apache-airflow

This project is an ETL project that extracts data from YouTube videos using the YouTube API. The extracted data includes video ID, title, like count, comment count, and comment text. The ETL process is orchestrated using Apache Airflow, and the transformed data is loaded into a CSV file, which is then stored in an AWS S3 bucket.

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