AI Study Series Part 4: Natural Language Processing (NLP)
Natural Language Processing (NLP) is the field of AI that deals with understanding and generating human language. NLP powers chatbots, translation tools, summarizers, and even search engines. This part of the series introduces you to the core concepts and where to learn them.
What is NLP?
NLP is a subfield of AI that enables machines to read, interpret, generate, and respond to human language in a useful way. It combines linguistics, computer science, and deep learning.
Core NLP Topics
- Tokenization and Word Embeddings
- Named Entity Recognition (NER)
- Sentiment Analysis
- Machine Translation
- Text Summarization
- Question Answering Systems
Learn NLP from Trusted Sources
- Harvard's CS50 AI with Python: Includes NLP-focused projects like sentiment analysis and question answering.
- DeepLearning.AI – NLP Specialization: A structured Coursera course that covers all core NLP tasks using TensorFlow.
- Fast.ai NLP Course: Fast, intuitive, and practical—build real NLP models fast.
- MIT OpenCourseWare: Advanced linguistics and NLP lectures from top researchers.
- Google AI Education: Free guides and code labs on NLP topics like BERT and Transformers.
Recommended NLP Libraries and Tools
- Hugging Face Transformers: Pretrained language models like BERT, GPT-2, and T5 ready to use.
- spaCy: Industrial-grade NLP library for building real-world pipelines.
- NLTK: Educational NLP toolkit for Python.
Visual Learning Resources
Watch real NLP applications and theory breakdowns on TED Talks, Vimeo, and Bilibili. Look for “Natural Language Processing,” “AI chatbots,” or “language models” to find relevant content.
What’s Next?
In Part 5: Computer Vision and Image Recognition, you’ll explore how AI sees and interprets the world using images and video.
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