This repository is a collection of my Machine Learning (ML) and Deep Learning (DL) projects, covering a wide range of domains including regression, classification, time-series forecasting, computer vision, and object detection.
Working on these projects has been a cornerstone of my journey as an AI Engineer.
They allowed me to:
- Develop expertise in data preprocessing, feature engineering, and handling noisy datasets
- Master a wide range of ML algorithms and build hybrid ensembles for optimal performance
- Gain deep knowledge of CNN architectures (LeNet, AlexNet, VGG16, ResNet, DenseNet, GoogLeNet, ZFNet)
- Apply evaluation techniques including accuracy, precision, recall, F1-score, confusion matrices, and training curves
- Build confidence in tackling complex and large-scale ML/DL tasks
Although this repository is being uploaded a bit later, it represents the culmination of everything I learned and practiced in ML and DL.
Each project here reflects not just an implementation, but a step in my growth — from understanding fundamentals to confidently applying advanced techniques.
Through these projects, I have mastered almost all key aspects of ML/DL, while continuing to learn and explore cutting-edge advancements.