/ML_Lab_Exercises

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ML_Lab_Exercises

Part - 1

  1. Function identification from plots
  2. Function transformation identification
  3. Introduction to break-even analysis
  4. Matrix solution with Numpy
  5. Visualizing Vectors
  6. Matrix Operations: Calculating the time taken for sunlight to reach earth each day
  7. Matrix Search
  8. Use of Matrices in performing linear equations
  9. Finding the probability of state transitions

Part - 2

  1. Timing vectorized operations in Numpy
  2. Data table manipulation
  3. The student dataset
  4. Visualization of probability distributions
  5. Activity: Analyzing the communities and crime dataset
  6. Using a string column to produce a numerical column
  7. Calculating descriptive statistics
  8. Practicing EDA
  9. Activity: Finding out highly rated strategy games

Part - 3

Write Python scripts to perform unsupervised clustering techniues i. K-means ii. E-M clustering

Part - 4 Write Python scripts to develop following Machine learning tasks on any chosen dataset i. Linear Regression ii. Logistic Regression iii. Bayesian Classifiers iv. Adaboost classifiers v. decision tree classifier

Part - 5 Write Python script to develop following Neural Networj models for classfication on any chosen dataset i. Simple Multilayer perceptron ii. Deep Neural Networks (CNN/RNN)