Working with Text Data: How Computers Understand Language
📰 Medium · ChatGPT
Learn how computers process text data to understand language, a crucial step in building language models and transformers
Action Steps
- Read about tokenization to understand how text is broken down into individual words or tokens
- Explore the concept of embeddings to learn how words are represented as vectors in a high-dimensional space
- Apply preprocessing techniques to text data to prepare it for use in language models
- Build a simple language model using a library like NLTK or spaCy to practice working with text data
- Configure a transformer model to use pre-trained embeddings and fine-tune it on a specific task
Who Needs to Know This
Data scientists and NLP engineers benefit from understanding how computers process text data to improve language model performance and build more accurate transformers
Key Insight
💡 Computers don't understand text, but can process it using techniques like tokenization and embeddings
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🤖 Did you know computers don't understand text? Learn how they process language and build better language models!
Key Takeaways
Learn how computers process text data to understand language, a crucial step in building language models and transformers
Full Article
Before we can build a transformer or train a language model, we must solve one fundamental problem: computers don’t understand text. Continue reading on Medium »
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