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)

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

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?