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3d_tree_reconstruction

The repository implements methods that deal with constructing accurate 3D reconstructions of dormant apple fruit trees. The depth images are gathered from real orchards and point clouds are generated. The point clouds are then merged together using Iterative Closest Point ICP algorithm. Then shape (circle, semi circle, cylinder) fitting is performed to get 3D model of the trees.

bme_project

This is a multiprocessing implementation of word2vec algorithm in Python from scratch without using any machine learning libraries.

buglocalization

The repository implements code for information retrieval based bug localization. The open source Terrier search engine is extended to implement the novel algorithms that deal with performing IR based bug localization.

clustering_dimreduction

The implementations in this repository deal with clustering and dimensionality reduction for MNIST digits dataset. Kmeans clustering algorithm is implemented. Also different hierarchical clustering algorithms are tested. We also play with the PCA and TSNE embeddings of the MNIST dataset.

cnn_classification

The repository implements the a simple Convolutional Neural Network (CNN) from scratch for image classification. I experimented with it on MNIST digits and COIL object dataset.

dquas

mapsd

MAPSD (Map for Software Development) contains techniques for constructing a map of the world based on software development activity.

minesoft

Mining software repositories to extract pairs of related terms

sakbarpu.github.io

Welcome to my github main page.

traditionalclassifiers

This repository implements the basic machine learning classifiers for the problem of Yelp reviews classification. We assume the problem to be a binary classification problem. The models implemented are Naive Bayes, Logistic Regression, Support Vector Machine (linear), Decision Trees, Bagged Decision Trees, Random Fforests, and Boosted Decision Trees.