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Climate analysis using data for Hawaii. Precipitation, station and temperature were all analyzed. After analyzing the data a Flask API was designed on the queries that had been developed. Skills Needed: Python, Pandas, Jupyter Notebook, Flask
A Flask based production level web app which uses Naive Bayes classifier to predict given SMS is spam or ham. Also contains jupyter notebook with basic data exploration and ml modelling.
Project begins with initial scraping using Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter. A gitpages is created with the python files.
Skincare recommendation android application that uses dataset from Kaggle and scrapped data from cosmetics websites to work a Tf-IDF vectorizer for content based filtering, and KNN and Decision trees for collaborative based filtering. The notebook also contains other approaches for POC including SVD. Backend APIs are based on Flask, Android appl…
A web application that scrapes Mars information from different websites. Tools: Jupyter Notebook, BeautifulSoup, Pandas, Requests/Splinter, MongoDB, Flask, HTML, and Python
Here in this project we can analysis or predict if the user has osteoporotic fracture or not by using some data. I made this project using Machine learning and a dataset. This model has 94% accuracy. This is easy to install just you need some essential libraries for ML and run it in notebook.
This repository is an application developed in Flask as BackEnd for connecting the Jupyter Notebook to the Hive Server and execute the queries and displays the results back in the UI
This repository contains code for analyzing and predicting outcomes in the Indian Premier League (IPL) cricket matches from 2008 to 2022. It includes data analysis notebooks, a prediction model, and a Flask-based web application for interactive predictions. Explore historical match data, gain insights, and make predictions on upcoming matches .
This project utilizes deep learning to detect pneumonia from chest X-ray images, offering both model training and real-time inference through Jupyter Notebooks and a Flask web application. With a focus on flexibility and user-friendliness, it empowers users to fine-tune model parameters and seamlessly deploy the trained model for accurate pneumonia