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Uber users often struggle with fluctuating ride prices and varying wait times. This project addresses these challenges by leveraging real-time data and machine learning models to predict the best times for booking Uber rides utilizing continuous learning.
This website analyzes the largest companies in the United States by revenue. You can explore various aspects of these companies, including revenue trends, employee distribution, industry comparison, and more.
The PhonePe Pulse Data Visualization project in Python extracts, transforms, and stores data from the PhonePe Pulse GitHub repository. It creates an interactive dashboard using Streamlit, Plotly, and other libraries to visualize the data. Users can explore various insights from the data spanning 2018 to 2023.
Heroku Streamlit deployment using the NYC MTA stations as the dataset. I scraped the opening date of each station and created a slider to modify the map by year. Check it out!
A dataset about mushrooms was analysed to classify them as edible or poisonous. The application is developed on streamlit and deployed with docker and heroku.
Zomato Data Visualization with Streamlit.The project include visualization of 9000+ data with 7 functional tools to visualize dataset .Streamlit Framework is combined with data visualization tools like Pandas, Plotly , Altair, Pydeck etc. to provide a dynamic interface to analyze data.