Repository containing the colab-notebooks of the course i did on deep learning from One-Fourth-Labs

Slides, exercises, and exams for my course "Natural Language Processing" (École Pour l'Informatique et les Techniques Avancées, 2024 and 2025)

A series of machine learning trigger bots for Counter-Strike: Global Offensive (CS:GO).

Animation Tweening of 3D vertex data using a Feed-Forward Neural Network.

Models of Mouse Vision: Self-supervised pre-trained networks and training code (PyTorch)

f1 race winner predictor

Node Classification with Graph Neural Networks

Example of how to use MATLAB Deep Network Designer to build deep learning solutions to two different problems: diabetes prediction and medical image classification.

Training Feedforward Neural Networks with Bayesian Hyper-Heuristics

A machine learning trigger bot for Quake3 Arena & Quake Live.

Simulating the dynamical behavior of an Eddy current brake using neural networks

This is a application that though a feed forward neural network allows a car to learn to drive

Attempts to take an image of a face and convert it to a 3D head.

Theory and practice of neural networks, deep learning and fuzzy logic. Excercises based on the course ECE447 of University of Thessaly.

Tensorflow Human Behavior Prediction Engine

A custom neural network built entirely from scratch using NumPy. Engineered with fully tested backpropagation, early stopping, and reproducible training architecture.

Sentiment classification: From ML to DL to very DL models

Gran-Prix is a high-performance, modular, and type-safe neural network framework built from the ground up in Rust. It evolves from simple conceptual models into a robust engine for building and training multi-layer perceptrons and beyond

A quick implementation of Fast Feed Neural Network that support reading JSON input and visualize the network in an image

Multi-layer feed-forward neural networks and auto-encoder network for MNIST dataset implemented from scratch