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Jupyter Notebooks for Machine Learning Lab for the syllabus of the Visveswaraya Technological University. Contains Jupyter Notebooks of 10 different Machine Learning programs and algorithms ranging from extremely basic to intermediate.

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Machine Learning Lab Notebooks

For the 2015 CBCS Scheme, Visvesvaraya Technological University (VTU)


Working programs are:

  1. FIND-S
  2. Candidate Elimination
  3. ID3
  4. Backprop
  5. Naive Bayesian Classifier (for dataset)
  6. Naive Bayesian Classifier (for documents)
  7. Bayesian Network (using Heart Disease data set)
  8. K-Means Clustering (EM Algorithm)
  9. K-Nearest Neighbors (Iris data set)
  10. Locally Weighted Regression

In case the notebooks aren't rendering on GitHub, use nbviewer. (Just paste the URL of the notebook from GitHub into URL input bar on their homepage)


To download the entire notebooks directory, clone the repo.

First, navigate to your desired directory

cd <your desired directory>

then do,

git clone https://github.com/pavanpej/ML-Lab.git

Data sets are included for programs that require them in their respective folders.

Some use the Scikit-learn library. Other documentation is written as part of the notebook.

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Jupyter Notebooks for Machine Learning Lab for the syllabus of the Visveswaraya Technological University. Contains Jupyter Notebooks of 10 different Machine Learning programs and algorithms ranging from extremely basic to intermediate.

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