This repository contains basic implementations of some common algorithms I had to implement for the SMAI, Fall'21 course at IIIT-H.
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01 Clustering: Implementation of K-Means and some experiments with different initialization techniques, distance metrics and finding optimal number of clusters.
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02 CNN: Training a basic image classifier using a CNN in pytorch.
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03 Decision Trees: Using decision trees on the WBC dataset and experimenting with basic parameters like number of layers, measure used for purity etc. Also, contains implementation of Random Forest Algorithm.
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04 RNN: Basic sentiment classification task using RNN and LSTMs and performance comparison between the two.
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05 SVM: SVM implementation using CVXPY
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06 KNN, logistic regression etc: Basic implementation of KNN and logistic regression