Simple Keras-inspired DeepLearning Framework implemented in Python with Numpy backend: MLP, CNN, RNN, RBF, SOM, DBN...

A series of 12 assignments/labs regarding Stochastic Processes and Machine Learning including a plethora of models and techniques implemented in Google Colab notebooks

From Markov Fields to Deep Belief Networks theory and experimentation on Google Landmark Recognition.

Cognition and Computation Course Project

🧠 Deep learning algorithms implemented from scratch using only NumPy — no frameworks, just math, backpropagation, and fundamentals.

A version of the learnergy package to deal with video datasets

Utilisation de modèles génératifs comme tâche prétexte pour pré-entrainement de DNN pour classification.

Uncover the secrets of deep learning with FashionDBN - implementing PyTorch's Deep Belief Network for accurate image classification and beyond.

This projects were made for the Machine Learning course at the AGH UST in 2024/2025. Obtained maximum grade 5.0.

Daft wrapper for easily creating Dynamic Bayesian Network plots

Makine Öğrenmesi dersi kapsamında geliştirilen Derin Öğrenme uygulamaları. CNN, RNN, DBN, RBM ve Autoencoder mimarileri

A repository for generating synthetic data (images) using various DL/ML models.

📄 Official implementation regarding the chapter "Fine-Tuning Deep Belief Networks with Harmony-Based Optimization".

This repository is dedicated to my collaboration in the "AUTOMOTIVE" Project. This project's objective is to development automatic face image/video-based drowsiness recognition.

The DBN compiler translates DBN source into SVG source file. The resulting SVG source files can then be loaded and executed on any web browser. (Pet project)

RBM and DBN over MNIST dataset

ECG Classification of Normal and Abnormal with GB-DBN Model (pytorch)

The software includes a dynamic bayesian network with genetic feature space selection, includes 5 econometric data.frames with 263 time series.