ImRCIFAR/Implementations at main · introspective321/ImRCIFAR · GitHub

Name		Name	Last commit message	Last commit date
parent directory ..
Demo-Code.ipynb		Demo-Code.ipynb
Multiclass_Single_Layer_Perceptron.py		Multiclass_Single_Layer_Perceptron.py
PCA_from_scratch.py		PCA_from_scratch.py
README.md		README.md
Support_Vector_Machines.ipynb		Support_Vector_Machines.ipynb
cat.jpg		cat.jpg
desicion_tree.py		desicion_tree.py
k_means_scratch.py		k_means_scratch.py
knn_classifier.py		knn_classifier.py
naive_bayes.ipynb		naive_bayes.ipynb
random_forest.py		random_forest.py
svm_scratch.py		svm_scratch.py

README.md

Following machine learning methods are being implemented from scratch

Dimensionality Reduction
- Principle Component Analysis [Done]
- K-Means Clustering Compression** [Done]
Perceptron
- Multiclass (Single Layer) Perceptron* [Done]
- Multilayer Perceptron** [Done]
Ensemble Learning** [Done]
K Nearest Neighbour** [Done]
Naive Bayes* [Done]
Logistic Regression (one-vs-all)* [Done]
Support Vector Machine** [Done]

*: Linear Decision Boundaries

**: Non Linear Decision Boundaries