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Natural Language Processing

NLP is Natural Language Processing the technology behind Home assistants and search engines.

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How to Actually Test a Chatbot (Not "The Answer Looked Fine")

How to Actually Test a Chatbot (Not "The Answer Looked Fine")

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5 min read
Language Models and Languages: Why "Multilingual" Is an Illusion of Equality

Language Models and Languages: Why "Multilingual" Is an Illusion of Equality

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7 min read
Dependency Parsing: How NLP Understands Sentence Structure

Dependency Parsing: How NLP Understands Sentence Structure

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8 min read
Day 14: FastText and Subword Embeddings

Day 14: FastText and Subword Embeddings

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5 min read
Day 13: GloVe: Global Vectors for Word Representation

Day 13: GloVe: Global Vectors for Word Representation

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6 min read
Where NLP Meets Recommendations

Where NLP Meets Recommendations

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5 min read
Part of Speech Tagging: How NLP Understands Grammar

Part of Speech Tagging: How NLP Understands Grammar

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8 min read
🧠 I Trained a Massive Word2Vec Model on 13 Billion Russian Fiction Words — Here’s What Happened

🧠 I Trained a Massive Word2Vec Model on 13 Billion Russian Fiction Words — Here’s What Happened

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4 min read
Day 12: Word2Vec Explained: Skip-Gram and CBOW

Day 12: Word2Vec Explained: Skip-Gram and CBOW

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5 min read
Sentiment Analysis of Apple Tweets: An NLP Approach

Sentiment Analysis of Apple Tweets: An NLP Approach

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2 min read
Was TinyStories the Domain or the Vocabulary?

Was TinyStories the Domain or the Vocabulary?

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4 min read
Day 15: Visualizing Embeddings with t-SNE and PCA

Day 15: Visualizing Embeddings with t-SNE and PCA

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5 min read
Tokenization in NLP: How Machines Break Down Text

Tokenization in NLP: How Machines Break Down Text

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8 min read
Day 11: Why One-Hot Encoding Fails: The Case for Embeddings

Day 11: Why One-Hot Encoding Fails: The Case for Embeddings

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3 min read
Day 10: Evaluation Metrics for NLP: Precision, Recall, F1, Confusion Matrix

Day 10: Evaluation Metrics for NLP: Precision, Recall, F1, Confusion Matrix

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5 min read
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