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alivaliyev

Config files for my GitHub profile.

ceng-240-introduction-to-python

Programming with Python for Engineers

ceng310-algorithms-and-data-structures

Textbook: Algorithms and Data Structures with Python, Michael H. Goldwasser, Michael T. Goodrich, Roberto Tamassia. These are my solutions for the homeworks and assignments for this course.

evaluation-the-quality-of-synthetic-data-set-for-fraud-detection

The objective of my experiment is to analyze the performance of Random Forest, Naive Bayes, Logistic Regression, and K-nearest neighbors machine learning models for evaluation of the utility of synthesized data for fraud detection.

informatika.edu.az

I present my solutions, written in the C++ programming language, for various problems that I have successfully resolved on the website informatika.edu.az.

ipsos-metu-stats-2023-datathon

ipsos-metu-stats-2023-datathon-preselection

math381-numerical-analysis-i

I would like to showcase the group projects that were completed by my friends and myself as part of our numerical analysis course.

math382-numerical-analysis-ii

We, a team of students, recently completed a series of projects as part of our numerical analysis course. These projects involved the application of various numerical methods to solve mathematical problems and analyze the results. Through these projects, we gained a deeper understanding of the concepts covered in the course and honed our skills in

math402-introduction-to-optimization

utility-of-synthetic-data-in-machine-learning-tasks.

In this repository, I tried to investigate the utility of synthetic data generated by DataSynthesizer and Synthetic Data Vault in machine learning tasks. I applied the Random Forest, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Naive Bayes algorithms to the synthetic data and made a comparison.