Exploratory data analyzing of Global Financial Database and loan borrowing prediction using PySpark
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Updated
Jun 13, 2024 - Jupyter Notebook
Exploratory data analyzing of Global Financial Database and loan borrowing prediction using PySpark
Car insurance prediction using Logistic Regression and the Naive Bayes
House sale price prediction using Linear Regression
Advanced Image Enhancement and Data Recovery: Superresolution Techniques and Missing Data Handling
This Project will perform linear regression on Automobiles MPG
Compute a moving root mean squared error (RMSE) incrementally.
Compute the root mean squared error (RMSE) incrementally.
Artificial intelligence (AI, ML, DL) performance metrics implemented in Python
[DACON Competition] experience Jeju specialities
experience Jeju specialities
This machine learning project focused on predicting food delivery times. The code emphasizes essential tasks such as data cleaning, feature engineering, categorical feature encoding, data splitting, and standardization to establish a solid foundation for building a robust predictive model.
Optimizing lighting distribution across regions by adjusting lamp powers.
Python, K-fold, RMSE, Pearson
An R package to apply affine and similarity transformations on vector layers (sp objects)
The dataset comprises data obtained from the 1990 census conducted in the state of California.
Delve into the exciting world of Applied Machine Learning to deliver personalized anime recommendations! This project is designed to help anime enthusiasts discover new series tailored to their unique preferences, enhancing their viewing experience.
Trains, tunes, and evaluates different regression models to develop a time-efficient, high-quality model for predicting car prices based on RMSE and CPU runtime.
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