Project: Deep Learning Implementation

Overview

This repository, Deeplearning-project, contains a Jupyter Notebook that summarizes and implements concepts from the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. The notebook includes theoretical insights and a deep learning project based on the book's methodologies.

Contents

• Summary of the book section: Key takeaways and explanations from the relevant chapters.
• Deep Learning Project: Application of deep learning techniques to a real-world dataset.
• Code Implementation: Step-by-step execution of deep learning models using Keras and TensorFlow.

Technologies Used

• Python
• Jupyter Notebook
• TensorFlow
• Keras
• Scikit-Learn
• NumPy
• Pandas

How to Use

1. Clone this repository:

   git clone https://github.com/Beshoy-Zaki/Deeplearning-project.git

2. Navigate to the project directory:

   cd Deeplearning-project

3. Open the Jupyter Notebook:

   jupyter notebook SemiColonGradProj.ipynb

4. Run the cells to execute the code and understand the implementations.

Prerequisites

Ensure you have the following dependencies installed:

pip install numpy pandas scikit-learn tensorflow keras jupyter

Or you can use colab directly.

Author

Beshoy-Zaki