Deep learning has revolutionized the field of Natural Language Processing (NLP) by enabling models to understand, generate, and manipulate human language with unprecedented accuracy. Below are key concepts and applications to get started:

Core Concepts

  • Neural Networks: The foundation of deep learning, using layers of nodes to learn patterns from data.
    neural_network
  • Word Embeddings: Techniques like Word2Vec or GloVe convert text into numerical vectors for machine learning.
    word_embeddings
  • Recurrent Neural Networks (RNNs): Designed for sequential data, ideal for tasks like language modeling.
    recurrent_neural_networks

Applications in NLP

  1. Text Classification
    text_classification
  2. Sentiment Analysis
    sentiment_analysis
  3. Machine Translation
    machine_translation

Next Steps

For deeper exploration, check out our NLP Overview Tutorial to understand the broader landscape of NLP techniques.