https://github.com/madhurimarawat/intelligent-data-analysis

This repository contains data analysis programs in the Python programming language.
https://github.com/madhurimarawat/intelligent-data-analysis

apriori-algorithm association-rule-mining birch-clustering comparation data-analysis data-pre dbscan-clustering description-of-code fp-growth-algorithm handling-missing-value histogram id3-algorithm j48-classifier k-means-clustering naive-bayes-classifier neural-network principal-component-analysis python students-acedemic-dataset visualization

Last synced: 3 months ago
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This repository contains data analysis programs in the Python programming language.

• Host: GitHub
• URL: https://github.com/madhurimarawat/intelligent-data-analysis
• Owner: madhurimarawat
• Created: 2023-09-13T17:25:54.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-28T15:39:01.000Z (over 1 year ago)
• Last Synced: 2025-01-15T01:16:52.821Z (4 months ago)
• Topics: apriori-algorithm, association-rule-mining, birch-clustering, comparation, data-analysis, data-pre, dbscan-clustering, description-of-code, fp-growth-algorithm, handling-missing-value, histogram, id3-algorithm, j48-classifier, k-means-clustering, naive-bayes-classifier, neural-network, principal-component-analysis, python, students-acedemic-dataset, visualization
• Language: Jupyter Notebook
• Homepage:
• Size: 2.08 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Intelligent-Data-Analysis

This repository contains data analysis programs in the Python programming language.

- **Data Exploration:** Intelligent data analysis involves thorough exploration of datasets to understand patterns, trends, and anomalies.

- **Machine Learning Algorithms:** It leverages machine learning techniques to build predictive models and extract insights from data.

- **Decision Support:** It assists decision-making processes by providing valuable insights and recommendations based on data analysis.

- **Data Visualization:** Intelligent data analysis often includes data visualization techniques to present findings in a more understandable and actionable format.

- **Continuous Improvement:** It is an iterative process, constantly refining models and analysis methods to improve accuracy and relevance.

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## Table Of Contents 📔 🔖 📑

1. Demonstration of different Pre-processing Techniques including Missing Value Handling and Data Discretization on Election Dataset.

2. Demonstration of Data Reduction Techniques including PCA and Histogram on Predict Students’ Dropout and Academic Success and Wine Quality Dataset.

3. Demonstration of classification Rules Process on Dataset of Choice using ID3 and J48 Algorithm in Python.

4. Implement the classification Rules Process on Dataset of Choice using Naive Baye’s Algorithm in Python.

5. Build a Neural Network model to predict whether Tumor is Malignant or Benign for Breast Cancer

Wisconsin (Diagnostic) Dataset using Python.

6. Demonstration of Clustering on Dataset of Choice using Simple K-means Algorithm in Python.

7. Demonstration of Clustering on Dataset of Choice using Simple DBSCAN Algorithm in Python.

8. Demonstration of Clustering on Dataset of Choice using Simple BIRCH Algorithm in Python.

9. Demonstration of Association Rule Generation on Groceries dataset for Market Basket Analysis using Apriori Algorithm in Python.

10. Perform comparative analysis of Apriori and FP-Growth Algorithms on Market Basket Analysis usingPython.

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## Thanks for Visiting 😄

Drop a 🌟 if you find this repository useful.



If you have any doubts or suggestions, feel free to reach me.



📫 How to reach me:    [![Linkedin Badge](https://img.shields.io/badge/-madhurima-blue?style=flat&logo=Linkedin&logoColor=white)](https://www.linkedin.com/in/madhurima-rawat/)