2014, Clustering and Support Vector Machines

From Rulesets to Transformers: A Journey Through the Evolution of SOTA in NLP

Mlearning.ai

APRIL 8, 2023

The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. These included the Support vector machine (SVM) based models. 2014) Significant people : Geoffrey Hinton Yoshua Bengio Ilya Sutskever 5. 2018) “ Language models are few-shot learners ” by Brown et al.

Natural Language Processing

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Embeddings in Machine Learning

Mlearning.ai

JUNE 8, 2023

Sentence embeddings can also be used in text classification by representing entire sentences as high-dimensional vectors and then feeding them into a classifier. Clustering — we can cluster our sentences, useful for topic modeling. How can we make the machine draw the inference between ‘crowded places’ and ‘busy cities’?

Machine Learning

Machine Learning Machine Learning Clustering Database

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From Rulesets to Transformers: A Journey Through the Evolution of SOTA in NLP

Embeddings in Machine Learning

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