In this breakout session from the PyTorch Conference 2022, we will be focusing on the Lightning framework, an open-source Python library that makes it easier to build and deploy production-ready AI applications using PyTorch. The session will cover the entire process of building AI models using Lightning, from training and evaluation to deployment and monitoring.
Lightning is a high-level abstraction for PyTorch that provides a way to organize and encapsulate PyTorch code, making it easier to experiment with different models, hyperparameters, and training strategies. It also provides a set of utilities for common tasks such as logging, model checkpointing, and distributed training.
The session will begin with an introduction to the Lightning framework and its key features. We will then delve into how to use Lightning to train and evaluate AI models on real-world datasets. We will cover topics such as data preprocessing, model architecture, loss functions, and optimizer choices.
Next, we will discuss how to deploy Lightning models in production environments. This will include topics such as model serialization, inference pipelines, and serving infrastructure. We will also cover best practices for monitoring and maintaining production AI applications.
Throughout the session, we will use hands-on examples to demonstrate how to use Lightning to build and deploy real-world AI applications. These examples will cover a range of use cases, from image classification and natural language processing to reinforcement learning and anomaly detection.
By the end of the session, you will have a solid understanding of how to use Lightning to build and deploy production-ready AI applications. You will also have the knowledge and skills to continue experimenting with Lightning on your own projects.
Overall, this breakout session is perfect for AI practitioners who want to take their PyTorch skills to the next level and build robust and scalable AI applications. Whether you are a beginner or an experienced AI engineer, you will benefit from the comprehensive and practical insights provided in this session.
