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SEASON
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  1. SEASON
    Natural Language Processing

    Natural Language Processing

    Teaching computers to understand language is one of the most challenging problems in AI. This season walks through the evolution of natural language processing, from early statistical models to modern transformers. Along the way, it tackles core NLP tasks — translation, sentiment analysis, information extraction — and highlights both the linguistic theory and practical engineering behind machines that read, write, and speak.

  2. EP 01

    Ancient Text Restoration

    12/1/2019

    Thea Sommerschield joins us this week to discuss the development of Pythia - a machine learning model trained to assist in the reconstruction of ancient language text.

    Thea Sommerschield
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  3. EP 02

    BERT is Shallow

    9/23/2019

    Tim Niven joins us this week to discuss his work exploring the limits of what BERT can do on certain natural language tasks such as adversarial attacks, compositional learning, and systematic learning…

    Tim Niven
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  5. EP 04

    BERT

    7/29/2019

    Kyle provides a non-technical overview of why Bidirectional Encoder Representations from Transformers (BERT) is a powerful tool for natural language processing projects.

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  6. EP 05

    BLEU

    3/23/2019

    Bilingual evaluation understudy (or BLEU) is a metric for evaluating the quality of machine translation using human translation as examples of acceptable quality results. This metric has become a wide…

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