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ml-models

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This project demonstrates the application of machine learning techniques to predict house prices based on various features. By analyzing the dataset, preprocessing the data, and selecting an appropriate model, we were able to achieve a high level of accuracy in predicting house prices. The trained model can be further refined and deployed.

  • Updated Apr 29, 2024
  • Jupyter Notebook

This dataset is used to detect the credit card fraud detection. This is a classification problem. This is an imbalanced dataset based on target variable. So In this Project, I will use encoding and decoding techniques to balanced dataset.

  • Updated Jun 2, 2023
  • Jupyter Notebook

Experience a comprehensive exploration of Spotify's musical landscape seamlessly transitioned from Tableau visualizations to SQL analysis. Dive into track inventory, streaming metrics, and sonic trends via interactive dashboards, while leveraging SQL queries for deeper insights into KPIs and cross-platform rankings.

  • Updated Jul 25, 2024
  • Jupyter Notebook

This project aims to develop a predictive model estimating insurance coverage costs for customers based on their attributes and product choices. The dataset includes transaction and quote details for policy purchasers. The objective is to predict quoted coverage costs, considering customer traits and 7 customizable product options.

  • Updated Aug 20, 2023
  • Jupyter Notebook

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