Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through the use of natural language. Deep Learning has revolutionized NLP by enabling machines to understand, interpret, and generate human language with remarkable accuracy.
Key Concepts
- Neural Networks: These are the building blocks of deep learning models. They mimic the human brain's ability to learn from data.
- Embeddings: These are dense vector representations of words, which capture the semantic meaning of words.
- Sequence Models: These models, such as RNNs and LSTMs, are designed to handle sequences of data, like sentences.
Applications
- Machine Translation: Translating text from one language to another using deep learning models.
- Sentiment Analysis: Determining the sentiment of a piece of text, whether it's positive, negative, or neutral.
- Text Classification: Categorizing text into predefined categories, such as news articles or product reviews.
Resources
For further reading on Deep Learning for NLP, check out our guide on Natural Language Processing.
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Deep Learning Neural Network
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