Popular Neural Networks Classification Algorithms implemented intuitively on Matlab and Python
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Kohonen Self Organizing Map showcasing weight updation to classify Iris Data Set into 3 categories Details: https://archive.ics.uci.edu/ml/datasets/Iris
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Logistic Regression
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Linear and Multivariate Polynomial Regression
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Reinforcement Learning Solutions for the book: Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Logistic Regression applied mainly from Andrew Ng's CS229 lecture notes and online tutorials. Applied on IRIS data for 2 features
Details of tutorials: http://nbviewer.jupyter.org/github/tfolkman/learningwithdata/blob/master/Logistic%20Gradient%20Descent.ipynb http://aimotion.blogspot.in/2011/11/machine-learning-with-python-logistic.html
This is a sample data set provided by HackerRank for the prediction of Office Prices based on 2 or more features. I have applied Multivariate Linear Regression and Polynomial Regression on this set using Normal Equation of Least Squares method in Matrix form.
Details of the Challenge: https://www.hackerrank.com/challenges/predicting-office-space-price
Multi Armed Bandit Solutions:
Details of the Plot: Reward Values over 1000 trials averaged for:
- Greedy (epsilon=0)
- Epsilon-Greedy (epsilon=0.01)
- Epsilon-Greedy (epsilon=0.1)
- Softmax (incomplete, temperature=0.00001)