Machine Learning Algorithm Practices

Python code for implementing Machine Learning algorithms from scratch with corresponding visualizations using Matplotlib.

Algorithms implemented

• Decision tree

• K-Means

• Gaussian mixture model

• Principal component analysis

• Fastmap

• Perceptron Learning Algorithm

• Pocket Algorithm

• Linear Regression

• Logistic Regression

• Back Propagation Neural Networks

• to be continued ☕

Visualizations:

Decision tree:

K-Means:

Gaussian mixture model:

Principal component analysis:

Fastmap :
(dimension reduction for non-numeric data)

Perceptron Learning Algorithm & Pocket Algorithm:
hyper plane generated:

Error count:

Linear Regression:

Logistic Regression:

Major Libraries Used :

1. Numpy (Praise Numpy!)
2. Matplotlib
3. Pands

Todos

• Deep Learning Practices
• Test ML on larger data set
• Rewrite earlier projects using Numpy and better OO design.

License

BSD