Python for Natural Language Processing (Intermediate)
This quest dives deep into the world of Natural Language Processing (NLP) using Python. As you embark on this journey, you'll learn how to leverage libraries like NLTK, spaCy, and Transformers to perform text analysis, sentiment detection, and entity recognition. You'll explore techniques such as tokenization, stemming, lemmatization, and part-of-speech tagging. Each module will include hands-on projects where you will build your own NLP models and apply them to real-world datasets. By the end of this quest, you will have a solid understanding of the NLP pipeline and be equipped to create applications that can understand and generate human language.
• Understand the fundamental concepts of Natural Language Processing.
• Utilize Python libraries like NLTK and spaCy for text processing.
• Implement machine learning models for sentiment analysis.
• Build a chatbot using NLP techniques and frameworks.
