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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. 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.

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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. 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.

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Automated Fine-Tuning of LLAMA2 Models on Gradient AI Cloud

Analytics Vidhya

Introduction Welcome to the world of Large Language Models (LLM). In the old days, transfer learning was a concept mostly used in deep learning. However, in 2018, the “Universal Language Model Fine-tuning for Text Classification” paper changed the entire landscape of Natural Language Processing (NLP).

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Who is Durk Kingma, Anthropic’s latest transfer from OpenAI?

Dataconomy

cum laude in machine learning from the University of Amsterdam in 2017. His academic work, particularly in deep learning and generative models, has had a profound impact on the AI community. However, in 2018, he transitioned to being a part-time angel investor and advisor to AI startups, and later rejoined Google Brain.

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Evolution of GPT series: The GPT revolution from 1 to 4 trillion

Data Science Dojo

Deep learning And NLP Deep Learning and Natural Language Processing (NLP) are like best friends in the world of computers and language. Deep Learning is when computers use their brains, called neural networks, to learn lots of things from a ton of information.

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How To Make a Career in GenAI In 2024

Towards AI

Later, Python gained momentum and surpassed all programming languages, including Java, in popularity around 2018–19. The advent of more powerful personal computers paved the way for the gradual acceptance of deep learning-based methods. CS6910/CS7015: Deep Learning Mitesh M.

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

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.