Introduction to Natural Language Processing

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The Interpretive Loop

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Search and Document Summarization

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Topic Modeling Graph

Figure 4

Named Entity Recognition

Corpus Development- Text Data Collection

Preparing and Preprocessing Your Data

Figure 1

The Interpretive Loop

Vector Space and Distance

Figure 1

The Interpretive Loop

Figure 2

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Figure 3

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Document Embeddings and TF-IDF

Latent Semantic Analysis

Figure 1

The Interpretive Loop

Figure 2

Maps with different projections of the Earth

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Image of drop-off of variance explained

Figure 4

Plot results of our LSA model

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Plot results of our LSA model, color-coded by author

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Plot results of our LSA model, revised with new axis labels

Intro to Word Embeddings

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Skipgram

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PCA Variance Explained

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Visualizing Word Embeddings with PCA

The Word2Vec Algorithm

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Single artificial neuron

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Linear Decision Boundary

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Multilayer neural network

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Hierarchical Feature Representations - Face Detection

Figure 5

Skipgram

Figure 6

Word2Vec Model Architecture (Skip-gram)

Figure 7

Image from Word2Vec research paper, by Mikolov et al

Training Word2Vec

Finetuning LLMs

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BERT fine-tune

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BERT fine-tune

Ethics and Text Analysis