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
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)
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)
WEEK 1 | 10 August Resources
What all i learnt?