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FreeAI/Machine Learningintermediate

Natural Language Processing

A guide on the fundamental concepts of NLP, from basic text cleaning to advanced topic modelling and project implementation with Python

2 weeksEN4 lessons457 enrolled

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Natural Language Processing

Course Curriculum

1 modules · 4 subjects · 4 lessons
01
A Practical Guide to Natural Language ProcessingAuto-generated curriculum based on a provided list of sessions and video URLs.
4 subjects
Foundations of NLPNew Description
1 lessons
  • Introduction to NLPThis lesson covers the fundamentals of NLP, from its booming relevance to foundational techniques like Regex and the NLP pipeline.
Text Pre-processing and Feature EngineeringExploring the crucial steps of preparing text data for machine learning models, including tokenization, stemming, and feature creation.
1 lessons
  • Text Cleaning and PreparationThis lesson covers essential data preparation steps like tokenization, stemming, and lemmatization, and compares popular libraries.
Text Representation and EmbeddingsMethods for converting text into numerical features that can be used by machine learning models.
1 lessons
  • Converting Text to DataThis lesson explores various text representation techniques, from simple Bag of Words to advanced Word Embeddings and their practical applications.
Practical ProjectsEnd-to-end projects that apply the NLP skills learned in the previous subjects.
1 lessons
  • Building E2E NLP ProjectsThis lesson culminates the curriculum with practical projects, including a chatbot and a Generative AI system.

Skill Track

AI/Machine Learning

AI/Machine Learning

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