Applied Natural Language Processing
Explore natural language processing techniques, from corpus operations to advanced neural networks, for applications in machine translation, topic modeling, and conversation systems.
Lauren Klein on Data Feminism - Tracing Linguistic Innovation
Exploring linguistic innovation and cultural change through data analysis, challenging traditional narratives of individual genius and highlighting collaborative processes in idea creation and dissemination.
Probabilistic Topic Models and User Behavior
Explore latent thematic structures in document collections and user behavior data. Learn how topic modeling algorithms can enhance predictions and understanding of collection organization.
Using Generative AI to Better Understand B2B Audiences: From Topic Modeling to Text Classification
Unlock the potential of Generative AI and ML for B2B audience understanding. Explore innovative techniques in topic modeling and text classification using LLMs to enhance marketing strategies and data-driven decision-making.
Design and Build Powerful LLM Agents - Valentina Alto
Unlock the potential of LLM agents: explore their design, construction, and evolution from single to multi-agent systems. Gain insights into GenAI workflows and key components of AI agents.
What is Feminist Data Science?
Explore feminist data science with Lauren Klein, examining how gender perspectives can reshape data analysis methods and interpretations in humanities research.
Quantifying Artistic Experiences: How Art Metadata Can Be Used to Understand Audiences' Encounters with Art
Explore computational analysis of art metadata to understand audience experiences and improve art viewing, using topic models, NLP, and image extraction techniques.
Recent Developments in Neural Search
Explore cutting-edge neural methods for semantic search, improving text search quality with pre-trained transformer networks and advanced deployment techniques.
Independent Finite Approximations for Bayesian Nonparametric Inference
Explore independent finite approximations for Bayesian nonparametric inference, comparing them to truncated finite approximations and analyzing their performance in real-world applications.
Agent-based Mixture of Experts and LLM-augmented Autonomous Agents - A Tutorial on Dynamic Expert Generation
Discover how to create specialized AI expert agents through dynamic prompting, enabling tailored solutions for complex tasks from code generation to artistic design using LLM-augmented systems.
Latent Dirichlet Allocation with Gibbs Sampling Explained
Comprehensive explanation of Latent Dirichlet Allocation (LDA) with Gibbs Sampling, covering topic modeling, posterior inference, and implementation details. Ideal for those interested in understanding this classic machine learning technique.
CMU Neural Nets for NLP 2018 - Document-Level Models
Explore document-level NLP models, covering language modeling, topic modeling, coreference resolution, and discourse parsing. Learn advanced techniques for analyzing and processing longer texts.
Topic Modeling Workshop for Beginners in Python
Learn topic modeling in Python using Gensim, spaCy, and NLTK. Covers data preparation, exploratory analysis, tokenization, LDA modeling, and evaluation techniques for beginners.
Arriving at an Understanding of Computational Linguistics' Virtues - Lecture 1
Explore computational linguistics' virtues in humanities research. Learn text analysis methods, content extraction, and meaning derivation from digital sources to enhance humanities scholarship.
An Introduction to Humanities Analytics in Three Examples
Explore humanities analytics through three examples, learning text analysis methods to extract meaning from digital sources and enable new scholarship in the humanities.
Topic Modelling with BERTopic - Applied NLP Tutorial
Learn topic modeling with BERTopic, extract insights from Kaggle notebooks, and create interactive visualizations. Master applied NLP techniques using transformers and c-TF-IDF for interpretable, dense topic clusters.
Latent Dirichlet Allocation Tutorial
Explore Latent Dirichlet Allocation in Python: Learn to implement this powerful topic modeling technique for text analysis and document classification.
Topic Modeling with R and Tidy Data Principles
Explore topic modeling in R using tidytext and stm packages, applied to Sherlock Holmes stories. Learn data preparation, text tidying, and model implementation techniques.
Topic Modeling for Spice Girls Lyrics
Explore topic modeling using R to analyze Spice Girls lyrics, uncovering hidden themes and patterns in their music through unsupervised machine learning techniques.
Poisson Random Fields for Dynamic Feature Models
Explore dynamic feature allocation models using Poisson random fields. Learn about the Wright-Fisher Indian Buffet Process and its application to topic modeling for time-stamped documents, with a focus on NIPS papers.
Introduction to NLP and Topic Modeling
Explore NLP basics, advanced techniques like word vectors, and topic modeling. Learn pre-processing, tools, and methodologies to start NLP modeling and understand topic analysis.