Python and Deep Learning Tutorials

• Welcome to the Python and Deep Learning Tutorials repository! This repository contains two versions of our tutorials: Legacy and Current. Each version is designed to help learners at different stages of proficiency, from beginners to more advanced users.

Structure

• Legacy version: Found in the legacy_materials folder, this includes tutorials ranging from basic linear regression models to implementing a VGG16 model.
• Current version: Located in the current_materials folder, this version covers topics from Python basics for beginners to implementing Convolutional Neural Networks (CNNs).

Getting Started

• To get started with these tutorials, clone this repository to your local machine or download the files directly.

git clone https://github.com/Sangh0/DeepLearning-Tutorial.git

• Navigate into the folder you want to explore and open the Colab files to start learning:

cd DeepLearning-Tutorial/current_materials

• Or run in Colab

Prerequisites

• To make the most of these tutorials, a basic understanding of Python programming is necessary. If you are new to Python, refer to the current_materials. The deep learning section requires a basic understanding of Python.

How to Use

• 1. Choose Your Version: Decide whether you want to start with the Legacy materials or the Current tutorials based on your skill level and learning goals. If you don't know Python, go to Current tutorials.
• 2. Open the Colab Files: Each folder contains Python files and .ipynb files that you can open with Google Colab or any Jupyter notebook files.
• 3. Follow Along: Each tutorial is self-contained and includes both explanations and code. You can read through the explanations and execute the code cells in order.

Contributing

• Contributions to this tutorial repository are welcome! If you have suggestions for improvements or additional tutorials, please open an issue or submit a pull request.