Welcome to my Deep Learning repository!
This is where I share my practical journey into deep learning — from learning the basics to building and experimenting with different models.
This repository includes:
- Implementations of deep learning models using PyTorch and TensorFlow
- Projects in computer vision and natural language processing
- Hands-on experiments with neural networks, CNNs, RNNs, and more
- Practice notebooks and notes to reinforce foundational concepts
My goal here is not to show perfection, but progress — learning one step at a time through building and experimentation.
- Python
- PyTorch / TensorFlow
- Jupyter Notebooks
- NumPy, Matplotlib, Pandas
- Scikit-learn (for preprocessing and evaluation)
- Building and understanding deep learning models
- Working with real-world datasets
- Avoiding overfitting and improving model performance
- Learning through code, debugging, and reflection
- 📫 Email: [email protected]
- 📊 Kaggle: Raghav Ramani
This repo is part of my consistent effort to grow in deep learning.
I'm still learning — suggestions, corrections, and ideas are always welcome.