The Machine Learning Library

These are the implementations of algorithms used in Machine Learning using numpy.

Following Algorithms have been included:

Name		Name	Last commit message	Last commit date
Latest commit History 20 Commits
Canny-Edge-Detection-Implementation		Canny-Edge-Detection-Implementation
Classification Measures		Classification Measures
Decision Trees		Decision Trees
Feature Scalling		Feature Scalling
KNN Classification		KNN Classification
Linear Regression		Linear Regression
Linear_Regression_Gradient_Descent		Linear_Regression_Gradient_Descent
Logistic Regression		Logistic Regression
NLP		NLP
Naive_Bayes		Naive_Bayes
PCA		PCA
Random Forests		Random Forests
Support Vector Machine		Support Vector Machine
CNN-MNIST.ipynb		CNN-MNIST.ipynb
Complex Boundaries Revisited.ipynb		Complex Boundaries Revisited.ipynb
Complex Boundaries self Implementation.ipynb		Complex Boundaries self Implementation.ipynb
GasPower_data.csv		GasPower_data.csv
Gradient Descent Revisited.ipynb		Gradient Descent Revisited.ipynb
Intro to Machine Learning Revisited.ipynb		Intro to Machine Learning Revisited.ipynb
Linear Regression Revisited, optimal coeffs, cost, coding LR1 and LR2.ipynb		Linear Regression Revisited, optimal coeffs, cost, coding LR1 and LR2.ipynb
Pandas Revised.ipynb		Pandas Revised.ipynb
README.md		README.md
answers.txt		answers.txt
boston_data.csv		boston_data.csv
data.csv		data.csv
predictedValues.csv		predictedValues.csv
predictedValues_GasPower.csv		predictedValues_GasPower.csv
titanic_test.csv		titanic_test.csv

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