NLP & Deep Learning: Master Text Preprocessing, Embeddings, Transformers, & LLMs for Advanced AI Applications.
Sub Category
- Other IT & Software
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Objectives
- Understand the fundamental concepts and challenges of Natural Language Processing.
- Master essential text preprocessing techniques, including tokenization, stemming, lemmatization, and stop-word removal.
- Apply various feature engineering methods for text data, such as Bag-of-Words, TF-IDF, and N-grams.
- Implement and utilize different types of word embeddings like Word2Vec, GloVe, and FastText.
- Build and evaluate traditional machine learning models for text classification and sentiment analysis.
Pre Requisites
- Basic proficiency in Python programming (variables, loops, functions, data structures).
- Familiarity with fundamental concepts of machine learning is helpful but not strictly required.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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