https://github.com/shibasishb2/supervised-learning-project

This project uses the most popular classification techniques to predict the outcomes after extensively working on EDA treating missing values and imbalanced data.
https://github.com/shibasishb2/supervised-learning-project

knn-classification linear-regression logistic-regression naive-bayes-classifier python svm

Last synced: about 2 months ago
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This project uses the most popular classification techniques to predict the outcomes after extensively working on EDA treating missing values and imbalanced data.

• Host: GitHub
• URL: https://github.com/shibasishb2/supervised-learning-project
• Owner: shibasishb2
• Created: 2024-03-10T14:48:37.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-07-29T13:12:55.000Z (5 months ago)
• Last Synced: 2024-07-29T16:44:52.306Z (5 months ago)
• Topics: knn-classification, linear-regression, logistic-regression, naive-bayes-classifier, python, svm
• Language: Jupyter Notebook
• Homepage:
• Size: 2.18 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Supervised-Learning-Project

This project uses the most popular classification techniques to predict the outcomes after extensively working on EDA treating missing values and imbalanced data. This project has two parts.

Part 1-Predicting the condition of the patient depending on the received test results on biomechanics features of the patients according to their current conditions. 

Part 2-Build an AIML model to perform focused marketing by predicting the potential customers who will convert using the historical database.

# Skills & Tools Covered

- Logistic Regression

- Naive Bayes

- KNN

- Classification

- Python

- SVM

- Linear regression