Welcome to the advanced section of our NLP tutorials! If you're looking to delve deeper into the world of natural language processing, you've come to the right place. Here, we'll cover some of the more complex topics and techniques in the field.

Topics Covered

  • Deep Learning for NLP
  • Text Classification
  • Sentiment Analysis
  • Named Entity Recognition
  • Language Modeling

Deep Learning for NLP

Deep learning has revolutionized the field of NLP. By using neural networks, we can train models to understand and generate human language. One popular deep learning model for NLP is the Transformer, which is used in models like BERT and GPT.

Deep Learning

For more information on deep learning for NLP, check out our Introduction to Deep Learning for NLP.

Text Classification

Text classification is a common task in NLP, where the goal is to categorize text into predefined classes. This can be used for tasks like spam detection, sentiment analysis, and topic classification.

  • Spam Detection
  • Sentiment Analysis
  • Topic Classification

Text Classification

To learn more about text classification, visit our Text Classification Tutorial.

Sentiment Analysis

Sentiment analysis involves determining the sentiment of a piece of text, whether it's positive, negative, or neutral. This is useful for understanding customer feedback, social media sentiment, and more.

Sentiment Analysis

For an in-depth look at sentiment analysis, see our Sentiment Analysis Tutorial.

Named Entity Recognition

Named Entity Recognition (NER) is the task of identifying and classifying named entities in text. Named entities can be people, organizations, locations, and more.

Named Entity Recognition

To explore NER further, check out our Named Entity Recognition Tutorial.

Language Modeling

Language modeling is the task of predicting the probability of a sequence of words. This is the foundation of many NLP tasks, including machine translation and text generation.

Language Modeling

For more on language modeling, read our Language Modeling Tutorial.

By exploring these advanced topics, you'll gain a deeper understanding of NLP and be well on your way to becoming an expert in the field. Happy learning!