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Andrew NG Machine Learning - Assignments with Python!

my solutions to Coursera Machine Learning course, using python

Assignments

  • ex1 - Linear Regression

    • ex1-oneVariable.ipynb : Linear regression (one variable), gradient descent and scikit learn
    • ex1-multipleVariables.ipynb : Linear regression (multiple variable), gradient descent and scikit learn
  • ex2 - Logistic Regression

    • ex2.ipynb : Two parts: Not regularized, Regularized (polynomial features), logistic regression using scikit learn is practiced in assignment 3
  • ex3 - Logistic Regression and Neural Networks

    • ex3-logistic.ipynb : Multi-Class logistic regression (mnist dataset), using gradient descent (Method 1) and scikit learn (Method 2)
    • ex3-neural.ipynb : Implementation of forward-propagation in order to find training accuracy of a given neural network
  • ex4 - Neural Networks

    • ex4.ipynb : A NeuralNetwork class, generalized to whatever network architecture user wants, using fmin_cg to minimize cost function
  • ex5 - Regularized Linear Regression and Bias vs. Variance

    • ex5.ipynb : Linear regression with regularization, learning curves, polynomial linear regression with plots and finding best lambda for our regularization.

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