Transformers with TensorFlow/PyTorch focuses on building and deploying transformer-based deep learning models using two of the most popular machine learning frameworks. It enables developers to implement advanced natural language processing solutions for tasks such as text classification, translation, summarization, and question answering. This training explains how transformer architectures work, including attention mechanisms, encoders, and decoders. It also covers model implementation using TensorFlow and PyTorch, along with training, fine-tuning, and evaluation techniques. You will learn how organizations use these frameworks to develop scalable and high-performance NLP applications. The course also highlights best practices for optimizing transformer models in production environments.
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