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Name: Selim Karaoglu
Type: User
Name: Selim Karaoglu
Type: User
Focusing on approximate inference methods and comparing their effectiveness on certain scenarios.
Bernoulli and Multinomial Naive Bayes classifiers are trained and tested on different datasets. We present and compare the accuracy scores for both Bernoulli NB and Multinomial NB models.
Experiment with PCA and CNN on CIFAR10 dataset, time series data analysis with LSTM and GRU
Experimenting with fully connected NNs and CNNs, using the Keras open source package.
Algorithms for “community” or cohesive subgraph detection are frequently used to analyze network representations of complex systems, and constitute an active area of methodological research. Algorithms for overlapping community detection are of particular interest, because it is often unrealistic to form strict partitions of natural systems, with at least some nodes participating in multiple clusters. However, the literature on overlapping communities does not distinguish different sources of potential overlap. This paper begins by discussing randomness, bridging nodes, and superimposed relational structures as three distinct sources of overlapping communities. It then focuses on the third source (neglected in the literature), by constructing test graphs that merge two distinct relational structures and comparing the communities identified by eight partition and overlapping community algorithms. Results show that most algorithms focus on the same source structure in each graph, ignoring the other, although a few algorithms find combined or nested communities from both structures.
This project focuses on the community structure analysis on graphs with multiple layers of community structures embedded in it. To conduct experiments on multiple layers of community structures in the graph, graphs that are based on the same nodes but wired with different edges are merged. Then the merged graph is analyzed by different techniques - such as community detection algorithms, overlapping community detection algorithms, nested community detection algorithms - to recover information about community structures set in the merged graph.
Userscript created for ICS465 class, week 2, group 3.
This project focuses on the implementation and evaluation of two supervised learning schemes: Decision Trees and Feedforward, Multilayer Neural Networks.
Decision Tree and Naive Bayes implementation and experiments.
This web application is designed to generate event files with event information provided by the user. This application is capable of create calendar event files with ".ics" extension that can be emailed or shared and read into the recipient's calendar applications.
Face recognition gained popularity in computer vision and the number of methods and techniques used in the process are increased. This paper provides experimental analysis on face recognition process with Triplet Loss function based network architectures. We implemented several different techniques to improve the overall computation time of the process - to be able to implement live detection on low computational resources - and we compared the results.
This report focuses on Fairness and Bias in Machine Learning (ML). Reviewed some researches that influenced the search of fairness in ML systems. We provide some insights to explain these concepts and how to avoid the bias and ensure fairness in ML system designs.
In this paper, we analyze the Forest Cover Dataset provided by UCI, build numerous classifiers to classify the forest cover type of a parcel of land, and evaluate the performance of the classifiers. To achieve this goal, we applied a step by step approach to the problem and explained the process thoroughly. We start the process with the data preprocessing. After adding id column and headers to the data in MS Excel, the data is stored in a “Comma Seperated Value” (.csv file) format. Following, definition of the libraries used in this project are provided. After applying data processing to the dataFrame, we examined and explained some features about the data that is crucial in the classification processes. In this process; plot of the data, correlation in the data columns, distribution of the data are the main focus. Furthermore, data is classified by different classifiers and these classifiers are cross validated with several hyperparameters to find the best tuning for each classifier. Afterwards we trained the classifiers with best hyperparameters and tested the performance on data. Finally we compared and analyzed the results.
This project creates a random melody and try to get a harmony between selected chord progression and evolved melody.
Evolutionary music project to provide harmonization between user selected chord progression and random melody in Mathematica.
Conducted the experiment on three part; first, evaluated the clustering results for Gaussian distribution datasets, following, utilized k-Means algorithm for image compression and employed the algorithms on Mall Customers dataset.
In this project, the main focus is the adaptation with nearest neighbor and local search methods.
Gradient Naive Bayes and Logistic Regression with Gradient, L1 and L2 regularization implementations from scratch
The Lord of the Rings novels adapted to cinema with three movies. This project analyzes the structure with scene by scene analysis of the movies, characters with details and some other factors affect the relationship between characters. These variables are used to create a network to see the relations in the Lord of the Rings cinematic universe.
Deep Learning Homework 1: Maximum Likelihood Estimation
Major Depression Disorder Analysis with Gene Expression and Demographic Symptom Data
Multi-armed bandits experiment with epsilon-greedy, UCB, Thompson sampling, Bayesian-greedy and HA-UCB
Simple Neural Network implementation with only numpy.
Trained and tested a Multinomial Naive Bayes algorithm on MNIST dataset, implemented PCA on MNIST dataset, then trained and tested the same Multinomial NB classifier with the results of different PCA applications.
In this paper, we implement a standard photometric stereo algorithm. With the albedo being unknown and not constant for the images, this program takes multiple images and light source direction information as an input and produce the albedo map, surface normals map, heights map and 3d plot of the surface for provided input. All the images used in this project are provided in the homework assignment and stored in "src" folder. Several output plots shown in the work are stored in the "out" folder.
Data Science Foundations class project from Selim Karaoglu and Jasper Green
Open-source keyboard firmware for Atmel AVR and Arm USB families
An Extended SIR Mathematical Model for Lumpy Skin Disease and Associated Properties
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.