ashishtele / Machine_Learning_hands_on_projects

Implementing Machine learning algorithms on available datasets

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R_Code

  1. Data Central Tendency
  2. Clustering Algorithms: K-Means and Hierarchical
  3. Visual data exploration
  4. Basic Image Processing: EBImage Package
  5. Bike Sharing Clustering: K-Means (package used: cluster, factoextra, tidyverse, readxl)
  6. Bike Sharing: Network graph creation (igraph and NetworkD3)
  7. Bike Sharing: PCA and t-SNE
  8. Attrition using Naive Bayes
  9. Purchase Prediction (Regression)
  10. Image classification using Keras feature extraction
  11. Fruit Image Classification - Keras (R)
  12. Churn using Keras
  13. Sunspot Keras
  14. UCI Yacht
  15. Vendor Volume Analysis Code
  16. R helper functions
  17. Power Point updates using R

Image source: https://github.com/rasbt supervised_learning_flowchart

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Implementing Machine learning algorithms on available datasets


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Language:R 100.0%