Natural Language Generation

Keelin M
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The basics of natural language generation (NLG), based on the curriculum of CIS 5300 – and created with a little help from NotebookLM! All episode cover images created with Flux.1-schnell

  1. 04/26/2025

    Practice Exam Review

    Practice Exam Review

    1 hr

  2. 04/17/2025

    Final Exam Review

    Final Exam Review

    1h 2m

  3. 04/03/2025

    Logical Representations of Sentence Meaning, Semantic Role Labeling & Information Extraction

    In this module, we'll continue our exploration of linguistic analysis of sentences rather than focusing on the structure of sentences like we did on the parsing module. To do so, we'll cover logical representations of sentence meaning, semantic role labeling and information extraction.

    23 min

  4. 03/31/2025

    Parsing and Dependency Parsing

    In this module, we'll delve more into the linguistics side of natural language processing. We'll take a look at different approaches to parsing and learn about the structure of sentences from a linguistics perspective.

    30 min

  5. 03/31/2025

    Dialogue Systems, Chatbots & Question Answering

    In this module, we will delve into two related NLP topics: dialogue systems and question answering.

    28 min

  6. 03/31/2025

    Machine Translation

    In this module, we will go over machine translation, one of the most important NLP applications, the challenges it involves, and how to evaluate machine translation models.

    29 min

  7. 03/30/2025

    Prompt Engineering, Instruction Following, and Using GPT

    In this module, we will delve into some of the capabilities of cutting edge pre-trained language models. We will explore the vital concepts of prompt engineering and instruction following. We'll first discuss the pre-train, prompt and predict paradigm, a new approach which questions whether fine tuning is even necessary. After. we'll cover several advanced prompting techniques such as few shot learning, instruction following and chain of thought prompting. These advanced techniques will provide us with a more efficient and more creative ways to harness the full potential of pre-trained language models.

    17 min

  8. 03/17/2025

    Encoder-Decoders, BERT and Fine-tuning

    In this module, we will cover encoder-decoder models, BERT, fine-tuning and masked language models. Understanding them will give you a good understanding of state-of-the-art NLP models, and why pre-trained large language models have become so important.

    22 min
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The basics of natural language generation (NLG), based on the curriculum of CIS 5300 – and created with a little help from NotebookLM! All episode cover images created with Flux.1-schnell

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