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Arpit Dwivedi edited this page Dec 1, 2020 · 2 revisions

1 Competition,1 project

  1. Part1: Flowchart with proper explanation of given algorithms.

    1.) SUPERVISED LEARINING

    • Classification
      • Random Forest
      • Decision Trees
      • Logistic Regression
      • Support Vector Machines
      • KNN
      • Naïve Bayes

    Usage

    • Regression
      • Linear Regression
      • Regularization Techniques (LASSO)
      • Polynomial Regression
      • Support Vector Regression
      • Decision Tree Regression
      • Random Forest Regression

    Usage

    2.) UNSUPERVISED LEARINING

    • Clustering
      • K-Means
      • K Nearest Neighbours

    Usage

  2. Part2: Supervised Learning

  3. Part3: Regression(popular algorithms)

  4. Part3: Regression notebook

  5. Part4: Performance Measure(Regression)

    • R-Squared
    • rmse(Root mean square error)
  6. Part5:Project: Boston House Prediction

  7. Part5:Project: Boston House Prediction Notebook

  8. Part6:Competition: Checking Accuracy for different models on boston house prediction

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