Accelerate Model Training with PyTorch 2.X
Build more accurate models by boosting the model training process
Created by Maicon Melo Alves
Unlock faster machine learning workflows by mastering optimization strategies with PyTorch. Discover how to spot and fix performance bottlenecks, streamline your data pipelines, and make the most of your hardware. Learn to train models efficiently so you can focus on achieving better results in less time.
Packt | Apr 2024 | 230 min
What You Will Learn
You will work through practical examples that show how to identify and resolve training slowdowns using PyTorch. By applying hands-on techniques, you will optimize data pipelines, use specialized libraries, and experiment with model simplification and mixed precision. Each step builds your confidence in applying these strategies to real projects.
Key Features
- Speed up model training by applying proven optimization techniques
- Leverage multicore systems and GPUs for distributed and parallel training
- Quickly test and refine models to improve accuracy and performance
Target Audience
Ideal for data scientists and machine learning practitioners with intermediate Python and PyTorch skills who want to train models faster and more efficiently. If you are looking to boost productivity and model quality without needing prior experience in distributed systems or advanced hardware, this course is designed for you.
