Made a simple handy webapp for travel planning and budgeting to help in the tedious task of organizing trips. Features include itinerary planning, saving your plans to your account and budgeting during the trip. The webapp is deployed on vercel and uses supabase as the backend.
Made With:
ReactJS
NextJS
Supabase
Build a machine learning model using various pre-built libraries to classify credit card fraud for a set of sample data. The SVM model used achieved an accuracy score of 73% and ROC area of 0.62. It is further validated using K-fold cross validation of 10.
Made With:
Python
Scikit Learn
Pandas
Numpy
Seaborn
Build a machine learning model using various pre-built libraries to predict scope 1 of carbon emissions for a manufacturing line. The decision tree model used achieved a R2 score of 99% and the online learning model achieved a R2 score of 96%. Various other models were also explored to detect outliers and provide a range of values for statistical process controls.
Made With:
Python
Scikit Learn
Pandas
Numpy
River ML
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