PyTorch Lightning Intermediate (Part 1)

Welcome to "PyTorch Lightning Intermediate (Part 1)"! This video is the first in our intermediate series designed to take your PyTorch Lightning skills to the next level. 🚀

In this video, we will cover:

1. **Review of Basics:** We'll start with a quick recap of the PyTorch Lightning basics covered in our previous videos. 🔄

2. **Advanced Training Techniques:** Dive into more advanced training techniques available in PyTorch Lightning, such as learning rate scheduling, gradient clipping, and using multiple GPUs. 🎓

3. **Custom Callbacks:** Learn how to create custom callbacks for more control over your training loop. 🛠️

4. **Logging and Visualization:** Get hands-on with TensorBoard and other logging tools to track your model's performance and visualize results. 📊

5. **Saving and Loading Models:** We'll cover best practices for saving and loading models, including how to resume training from a checkpoint. 💾

This video is perfect for those who have a basic understanding of PyTorch Lightning and want to leverage its full potential for their machine learning projects. So, grab a cup of coffee ☕ and let's get started!

Don't forget to like 👍, share 🔄, and subscribe 🔔 to our channel for more advanced tutorials on AI and machine learning. Happy learning! 🎉

**Disclaimer:** ⚠️ This video is for educational purposes only. It is not a substitute for professional advice or help and should not be relied on for making decisions. All the information provided in the video is believed to be accurate and reliable; however, we do not accept any responsibility for errors, omissions, or adverse effects arising from its use.