Gopinath Asokan's repositories
AI-Powered-Resume-Analyzer-and-LinkedIn-Scraper-with-Selenium
Developed an AI-based application using Streamlit to facilitate comprehensive resume analysis and it provides summarization, strengths, weaknesses, suggestions, and job title recommendations.
Youtube-Data-Harvesting-and-Warehousing
This repository hosts a project that enables efficient YouTube data extraction, storage, and analysis. It leverages SQL, MongoDB, and Streamlit to develop a user-friendly application for collecting and visualizing data from YouTube channels.
Airbnb-Analysis-with-Tableau
Built an interactive Tableau dashboard to analyze the Airbnb data extracted from MongoDB Atlas. Developed a Streamlit application for trend analysis, pattern recognition, and data insights using EDA. Explored variations in price, location, property type, and seasons through dynamic plots and charts.
Industrial-Copper-Modeling
We harness the power of machine learning and data analysis to real challenges in the copper industry. Our documentation covers data preprocessing, feature engineering, classification, regression, and model selection. Discover how we've optimized predictive capabilities for manufacturing solutions.
Bird-Sound-Classification-using-Deep-Learning
Constructed an advanced deep learning model utilizing TensorFlow and CNN to precisely classify bird species from audio inputs. Leveraging Librosa for audio processing, the model is trained on extensive bird sound datasets to ensure robust performance. Integrated with Hugging Face, our application facilitates seamless uploading of bird sound samples
Library-Management-Data-Structure
This algorithm is designed to assist in the management of books in a library. It provides functionality to track books, lend them to users, and manage the book database.
Phonepe-Pulse-Data-Visualization-and-Exploration
Developed a Streamlit application for analyzing transactions and user data from the Pulse dataset. Explored data insights on states, years, quarters, districts, transaction types, and brands through EDA. Visualized trends and patterns using plots and charts to optimize decision-making in the Fintech industry.
Rental-Property-Price-Prediction-using-Machine-Learning
Empower your real estate decisions with our data-driven model, delivering precise rental predictions for landlords and comprehensive insights for tenants in a dynamic market landscape.
Voice-AI-Automatic-Speech-Recognition
Developed a Marathi speech-to-text application using the Hugging Face whisper ASR models. Trained the model with a custom audio dataset and fine-tuned it for optimized performance. Deployed the model on the Hugging Face Model Hub, achieving a WER of 0.74 for the base model.
Analysis-on-Amazon-Prime-Videos-Using-Tableau
Explore Amazon Prime Video with Tableau! Gain valuable insights into content library, user engagement & preferences. Interactive dashboards and captivating visualizations reveal the magic of your favorite entertainment. Uncover data-driven stories now!
BizCardX-Extracting-Business-Card-Data-with-OCR
Effortless Business Card Data Management Revolutionize business card data handling with BizCardX. Extract, store, and manage contact details seamlessly using OCR and PostgreSQL integration. Experience the future of efficient information management.
Educational-Management-System
An IIT Internship project designed to streamline administrative and academic processes in educational institutions, offering automation, communication tools, and real-time insights for enhanced efficiency and educational experience.
IMDB-Movie-Analysis-with-PowerBI
Developed an interactive Power BI dashboard to analyze the factors influencing IMDB movie success. Statistical analysis of genres, language, duration, director, and budget, revealing impact on IMDB scores. Provided valuable insights to producers, directors, and investors for decision-making in the film industry.
Potato-Disease-Classification-using-Deep-Learning
Developed a deep learning model using TensorFlow and CNN to accurately identify diseases in potato plants, optimizing crop health and yield. The model distinguishes between diseases such as early blight, late blight, and healthy plants from images with precision.
Retail-Sales-Analysis-and-Forecast-using-Machine-Learning
Built a predictive machine learning model using a Streamlit application to predict weekly sales. Model achieved 97.4% accuracy and analyzed trends, patterns, and data insights using EDA. Compared various features and identified key contributors with a significant impact on prices.
Diabetes-Prediction-using-Machine-Learning
Experience predictive healthcare with our Streamlit app. Utilizing Random Forest, our tool analyzes medical data to assess diabetes risk swiftly. Ideal for healthcare professionals and researchers, this user-friendly app simplifies risk evaluation. Join us in the fight against diabetes.