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Transformer Models: The future of Natural Language Processing

Data Science Dojo

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. Learn more about NLP in this blog —-> Applications of Natural Language Processing The transformer has been so successful because it is able to learn long-range dependencies between words in a sentence.

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Transformer Models: The future of Natural Language Processing

Data Science Dojo

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. Learn more about NLP in this blog —-> Applications of Natural Language Processing The transformer has been so successful because it is able to learn long-range dependencies between words in a sentence.

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

Released in 2020, AlphaFold leverages deep learning algorithms to accurately predict the 3D structure of proteins from their amino acid sequences, outperforming traditional methods by a significant margin.

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Create and fine-tune sentence transformers for enhanced classification accuracy

AWS Machine Learning Blog

These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. For this demonstration, we use a public Amazon product dataset called Amazon Product Dataset 2020 from a kaggle competition.