📘 AM505PC

Machine Learning Lab

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ML Lab Experiment 1 to 5

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ML Lab Experiment 1 to 9

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Syllabus Overview

List of Experiments

1. Compute Central Tendency Measures

  • Mean
  • Median
  • Mode
  • Measure of Dispersion
  • Variance
  • Standard Deviation

2. Study of Python Basic Libraries

  • Statistics
  • Math
  • Numpy
  • Scipy

3. Study of Python Libraries for ML Applications

  • Pandas
  • Matplotlib

4. Implement Simple Linear Regression in Python

5. Implement Multiple Linear Regression for House Price Prediction using sklearn

6. Implement Decision Tree using sklearn and perform parameter tuning

7. Implement K-Nearest Neighbors (KNN) using sklearn

8. Implement Logistic Regression using sklearn

9. Implement K-Means Clustering

10. Performance Analysis of Classification Algorithms on a Specific Dataset (Mini Project)

Machine Learning Lab Notes