TensorFlow and Deep Learning Fundamentals with Python

Welcome to this repository focused on TensorFlow and Deep Learning fundamentals!

This repository explores the concepts covered in the following YouTube videos:

Video 1: [part-1] (https://youtu.be/tpCFfeUEGs8?si=lp4adyKkcTC5GVgI)

Video 2: [part-2] (https://youtu.be/ZUKz4125WNI?si=0-il7WZMOHq0D0qy)

These videos provide a fantastic introduction to building and training neural networks using TensorFlow.

What's Included?

Jupyter Notebooks (.ipynb) that walk you through the code and concepts presented in the videos.

Notes for the video tutorials. Check out the complete notes (Or fork a copy if needed!) provided by @mrdbourke.

Project Structure:

Each Jupyter Notebook corresponds to a specific video in the playlists. The notebooks are well-commented and designed to be clear and easy to follow.

Feel free to:

• Run the existing notebooks to gain hands-on experience.
• Modify the code to experiment with different parameters and concepts.
• Contribute your own notebooks or improvements (pull requests welcome!).

Get Started:

1. Clone this repository.
2. Open Google colab and navigate to the desired notebook.
3. Run the code cell by cell or experiment with modifications.

Happy learning!