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An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
This Project is a part of Data Science Nanodegree Program by Udacity in collaboration with Figure Eight. The initial dataset contains pre-labelled tweet and messages from real-life disasters. The aim of this project is to build a Natural Language Processing tool that categorize messages.
This project focuses on building end-to-end machine learning pipeline using AWS SageMaker to predict the price range of mobile phones based on their specifications, enhancing consumer decision-making and streamlining the development process.
A deployed machine learning model that has the capability to automatically classify the incoming disaster messages into related 36 categories. Project developed as a part of Udacity's Data Science Nanodegree program.
Collaborative team machine learning project classifying reviews scraped from the IMDB website as either positive or negative using sentiment classification. Tools used: BeautifulSoup and Splinter to scrape reviews, Pyspark, SQLAlchemy and Heroku.