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We're here to help you find itThe course begins with an overview of PyTorch, including model classes, datasets, data loaders and the training loop. Next, it covers the role and power of transfer learning, along with how to use it with pretrained models. Practical lab exercises cover multiple topics including: image classification, object detection, sentiment analysis, text classification, and text generation/completion. Learners also will use their data to fine-tune existing models and leverage third-party APIs.
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Certainly! Here are the minimum required prerequisites for successfully undertaking the PyTorch Essentials: An Applications-First Approach (LFD273) course:
With these prerequisites, learners will be well-prepared to dive into the practical applications of PyTorch in this course!
PyTorch Essentials: An Applications-First Approach (LFD273) equips learners with practical skills in PyTorch for developing AI applications, targeting individuals eager to enhance their machine learning expertise.
Introduction:
The PyTorch Essentials: An Applications-First Approach (LFD273) course provides a hands-on introduction to PyTorch, focusing on practical applications in deep learning and helping students master essential concepts for developing AI models.
Learning Objectives and Outcomes:
