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A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. This breakthrough has profound implications for drug development, as understanding protein structures can aid in designing more effective therapeutics.
Transformer models are a type of deeplearning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.
Transformer models are a type of deeplearning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.
Sentence transformers are powerful deeplearning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. For this demonstration, we use a public Amazon product dataset called Amazon Product Dataset 2020 from a kaggle competition.
Through the explainability of AI systems, it becomes easier to build trust, ensure accountability, and enable humans to comprehend and validate the decisions made by these models. For example, explainability is crucial if a healthcare professional uses a deeplearning model for medical diagnoses. References Castillo, D.
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