Building NLP models with Amazon SageMaker

Organizations have to manage massive volumes of voice and text data from various communication channels. Some use NLP to automatically process this data, analyze the intent or sentiment in the messages, and respond in real-time to human communication. But NLP models often consist of hundreds of millions of model parameters. Thus building, training, and optimizing them may require a lot of time, resources, and skills. This session outlines how Amazon SageMaker helps you to quickly build and train NLP models. We share the different distributed training and inference for large language models on Amazon SageMaker for use cases such as sentiment analysis, text summarization, and text classification.

Speaker: Tapan Hoskeri, Principal Solutions Architect, AWS India