Basic Machine Learning Implementation with Python and Numpy

This repository contains implementations of basic machine learning algorithms in Python and Numpy. All algorithms are implemented from scratch without using additional machine learning libraries. The intention of these notebooks is to provide a basic understanding of the algorithms and their underlying structure, not to provide the most efficient implementations.

Name		Name	Last commit message	Last commit date
.ipynb_checkpoints		.ipynb_checkpoints
README_files		README_files
figures		figures
BayesianClassifier.ipynb		BayesianClassifier.ipynb
Binary Naive Bayes.ipynb		Binary Naive Bayes.ipynb
Gaussian Discriminant Analyses.ipynb		Gaussian Discriminant Analyses.ipynb
Gaussian Naive Bayes.ipynb		Gaussian Naive Bayes.ipynb
ID3.ipynb		ID3.ipynb
KMeans.ipynb		KMeans.ipynb
Linear Regression Implementation from scratch.ipynb		Linear Regression Implementation from scratch.ipynb
Linear Regression with Newtons Method.ipynb		Linear Regression with Newtons Method.ipynb
Linear_reg.ipynb		Linear_reg.ipynb
Logistic Regression with Newtons Method.ipynb		Logistic Regression with Newtons Method.ipynb
Logistic Regression.ipynb		Logistic Regression.ipynb
Momentum in ML.ipynb		Momentum in ML.ipynb
Multi Class Gaussian Discriminant Analyses.ipynb		Multi Class Gaussian Discriminant Analyses.ipynb
Multi Class Logistic Regression with Newtons Method.ipynb		Multi Class Logistic Regression with Newtons Method.ipynb
Multi Class Logistic Regression.ipynb		Multi Class Logistic Regression.ipynb
Multinomial Naive Bayes.ipynb		Multinomial Naive Bayes.ipynb
Naive Bayes Implementation.ipynb		Naive Bayes Implementation.ipynb
Perceptron.ipynb		Perceptron.ipynb
README.md		README.md
Wrapper Method For Feature Selection - Forward and Backward .ipynb		Wrapper Method For Feature Selection - Forward and Backward .ipynb
book_rec_knn.ipynb		book_rec_knn.ipynb
gaussian_naive_bayes.py		gaussian_naive_bayes.py
gda.py		gda.py
kmeans.ipynb		kmeans.ipynb
kmeans.py		kmeans.py
lwlr.ipynb		lwlr.ipynb
naive_bayes.py		naive_bayes.py
spam filter.ipynb		spam filter.ipynb
svm.ipynb		svm.ipynb
train_test_split.pyc		train_test_split.pyc
utils.py		utils.py
utils.pyc		utils.pyc

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