About this podcast
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
Episodes
- Logical Representations of Sentence Meaning, Semantic Role Labeling & Information Extraction · 23 min · Season 1 Episode 14In 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…
- Parsing and Dependency Parsing · 30 min · Season 1 Episode 13In 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…
- Dialogue Systems, Chatbots & Question Answering · 28 min · Season 1 Episode 12In this module, we will delve into two related NLP topics: dialogue systems and question answering.
- Machine Translation · 29 min · Season 1 Episode 11In 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.
- Prompt Engineering, Instruction Following, and Using GPT · 17 min · Season 1 Episode 10In 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…
- Encoder-Decoders, BERT and Fine-tuning · 22 min · Season 1 Episode 9In 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…
- Transformers and Neural Text Generation · 20 min · Season 1 Episode 8In this module, we will cover transformers and pre-trained language models, and text generation. For the latter section, we will be joined by guest lecturer and Penn PhD…
- Parts of Speech & Grammars · 23 min · Season 1 Episode 7In this module, we're going to cover part of speech tagging. This is a fundamental task in natural language processing and has traditionally been used in a variety of…
- Neural Language Models · 18 min · Season 1 Episode 6In this module, we'll take a look at neural network based language models, which, unlike the previous N-gram based language models that we looked at earlier, use word embedding…
- Vector Space Models · 17 min · Season 1 Episode 5This week, we will continue our exploration of vector space semantics and embeddings. We'll begin the module by wrapping up word embeddings and discussing bias in vector space…
- Vector Space Semantics · 21 min · Season 1 Episode 4In this module, we'll begin to explore vector space semantics in natural language processing. (This will continue into next week.) Vector space semantics are powerful because…
- Review of Probabilities & N-gram Language Models · 14 min · Season 1 Episode 3In this module, we are going to cover essential topics that will allow us to move into important tasks in NLP: a review of probability and defining a probabilistic model. We will…
- Text Processing & Logistic Regression · 17 min · Season 1 Episode 2In this module, we'll begin with delving into text preprocessing. We'll go through tasks that transform an unstructured text into a structured format that we can analyze via…
- Text Classification, Sentiment Analysis, and Regular Expressions · 14 min · Season 1 Episode 1In this module, we’ll get started by looking at a classic natural language processing problem: text classification. Using the example of sentiment analysis, where we can…
