Artificial Intelligence
AI Model Development & Training
A collection of experiments and projects focused on machine learning, neural networks, generative AI, and model training. This work involved designing architectures, preparing datasets, training models, and exploring how modern AI systems learn and generate information.
Focus
Machine Learning & AI Research
Technologies
Python, PyTorch, NumPy
Areas
Neural Networks, GANs, LLMs
About The Project
My goal was to gain a deeper understanding of how modern AI systems work by building and training models from the ground up. Rather than treating machine learning as a black box, I explored how data flows through neural networks, how training affects model performance, and how different architectures solve different problems.
Through experimentation with language models, generative networks, and custom architectures, I developed practical experience with the entire machine learning workflow—from data preparation to model evaluation.
Areas Explored
- • Training custom neural networks for text and data processing
- • Building and experimenting with generative adversarial networks (GANs)
- • Learning the workings behind large language models
- • Dataset preparation and preprocessing pipelines
- • Evaluating model performance and training behavior
Skills Used
Machine Learning
Understanding training processes, optimization, and model evaluation.
Python Development
Building training pipelines, tools, and AI applications.
Data Processing
Preparing and transforming datasets for machine learning.
Problem Solving
Debugging training issues and improving model performance.