A structured collection of deep learning implementations and practical projects focused on building strong theoretical understanding and real-world model development skills.
🚀 Overview *This repository demonstrates hands-on experience with: *Designing and training neural networks *Implementing modern deep learning architectures *Optimizing models for performance and generalization *Applying models to real-world datasets
🔍 Core Areas *Artificial Neural Networks (ANN) *Convolutional Neural Networks (CNN) *Recurrent Neural Networks (RNN, LSTM, GRU) *Transformer Architectures *Optimization & Regularization Techniques
🛠 Tech Stack *Python *NumPy, Pandas *Scikit-learn *TensorFlow / Keras *PyTorch