https://github.com/ramyaragupathy/coursera

Solutions to Coursera learning tracks
https://github.com/ramyaragupathy/coursera

coursera stanford-machine-learning

Last synced: 13 days ago
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Solutions to Coursera learning tracks

• Host: GitHub
• URL: https://github.com/ramyaragupathy/coursera
• Owner: ramyaragupathy
• Created: 2018-03-14T11:27:08.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-04-09T03:07:18.000Z (almost 7 years ago)
• Last Synced: 2024-11-07T15:52:55.346Z (2 months ago)
• Topics: coursera, stanford-machine-learning
• Language: Matlab
• Size: 20.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Coursera

Solutions to Coursera learning tracks

## Machine Learning

- Loading data: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.m#L41) | [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.py#L38)

- Vectorisation of data: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.m#L42) | [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.py#L39-L40)

- Plotting a graph from data: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/plotData.m) | [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.py#L39-L40)

### Linear Regression 

- Cost Computation: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/computeCost.m) | [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.py#L19-L22)

- Gradient Descent: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/gradientDescent.m) | [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1.py#L25-L34)

- Feature Normalisation: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/featureNormalize.m) | [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1_multi.py#L10-L22)

- Normal Equations: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/normalEqn.m) |  [Python](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex1/ex1_multi.py#L25-L26)

### Regularised linear regression

- Cost Computation: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex5/linearRegCostFunction.m) | Python

- Learning Curve: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex5/learningCurve.m) | Python

- Polynomial features: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex5/polyFeatures.m) | Python

- Validation curve: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex5/validationCurve.m) | Python

### Logistic Regression

**Binary Classification**

- Sigmoid: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex2/sigmoid.m) | Python

- Cost Function: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex2/costFunction.m) | Python

- Prediction Function: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex2/predict.m) | Python

- Regularised cost: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex2/costFunctionReg.m) | Python

**Multiclass classification**

- Regularised cost: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex3/lrCostFunction.m)| Python

- One-vs-all classifier training: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex3/oneVsAll.m) | Python

- One-vs-all classifier prediction: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex3/predictOneVsAll.m) | Python

### Neural Networks

- Sigmoid Gradient: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex4/sigmoidGradient.m) | Python

- Prediction: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex3/predict.m) | Python

- Cost Function: [Octave](https://github.com/ramyaragupathy/Coursera/blob/master/Machine%20Learning/ex4/nnCostFunction.m) | Python