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Machine Learning Specialization

1. Machine Learning with Python(audit) Resources

What all i learnt?

  • In this audit course, i have implemented the supervised and unsupervised learning algorithms
  • Tuning the hyper parameters

2. Machine Learning Foundation

WEEK 1 | 20 July Resources

  • Week 1 offers the basic intoduction about Machine learning, how it evolved
  • Introduction to turicreate, SFrame and its basic implementation
  • Solved quiz questions
    Note: Check out the Resources to access .ipynb, data files and other materials.

WEEK 2 | 21 July | Use Case 1 Resources

What all i learnt?

  • Linear Regression use case approach and its other applications
  • How to load .sframe data file
  • Data exploration using turicreate.SFrame
  • Train test split of SFrame data file
  • Creating simple regression model using one/set of independent varibales
  • Training the model, and evaluating it on test_data
  • solved quiz questions
    Note: Check out the Resources to access .ipynb, data files and other materials.

WEEK 3 | 26 July | Use Case 2 Resources

What all i learnt?

  • linear Classifier (binary classificatio)

Deep Learning Specialization

1. Neural Networks and Deep learning

WEEK 1 | 27 July Resources

What all i learnt?

  • In this week we have introduction to neural networks and its examples
  • Check the hand written notes for more information

WEEK 2 | 27 July Resources

What all i learnt?

  • Logistic regression (binary classification)
  • Gradient Descent in Logistic Regression, Cost Funtion
  • Vectorization

WEEK 3 | 1 August Resources

What all i learnt?

  • Forward Propagation
  • Backward Propagation
  • Gardients and updating the weights and bias
  • single hidden layer neural network

WEEK 4 | 5 August Resources

What all i learnt?

  • L layered Neural Network
  • Forward and Back Propagations
  • Gardients and updating the weights and bias
  • Implementing L layer neural network for a Simple Classification Problem (Cat vs no-Cat)

2. Improving Deep Neural Networks (Hyperparameter tuning, Regularization and Optimization)

WEEK 1 | 10 August Resources

What all i learnt?