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657 tutors in 31 topics, built by 75 teachers. Each one follows a lesson plan its teacher wrote.

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Named entity recognition in practice

Named entity recognition in practice

Extract people, places, organisations and custom entities from text, and evaluate the results properlyIntermediateNLP4.7(3)79 lessonsSample
Nadia Haddad$7
Machine translation: how it works and fails

Machine translation: how it works and fails

Understand how machines translate, judge translation quality and know when a human translator is neededAll levelsNLP4.3(3)74 lessonsSample
Nadia Haddad$6
Question answering, from extractive to generative

Question answering, from extractive to generative

Understand how QA systems find, read and generate answers, and how to tell when they should abstainIntermediateNLP4.7(3)56 lessonsSample
Mateo Rojas$7
Summarisation systems and their failure modes

Summarisation systems and their failure modes

Build and judge summaries that stay faithful to the source, from short notes to long reportsAll levelsNLP4.7(3)46 lessonsSample
Mateo Rojas$6
RNNs, LSTMs and why transformers took over

RNNs, LSTMs and why transformers took over

Understand recurrent networks, their gates and limits, and the real reasons attention replaced themIntermediateDeep learning4.5(2)32 lessonsSample
Nikolai Sorin$7
Evaluating generated text

Evaluating generated text

Measure the quality of generated text with metrics, people and model judges, and know each one's limitsIntermediateEvaluation and testingNew
Mateo Rojas$8
NLP for multilingual and low resource languages

NLP for multilingual and low resource languages

Build and evaluate language technology for languages that most datasets and models leave behindAll levelsNLPNew
Nadia Haddad$7
Topic discovery and text clustering

Topic discovery and text clustering

Find themes in large text collections and check that the topics you found are real and usefulIntermediateData science and statisticsNew
Nadia Haddad$7