Master Natural Language Processing with this comprehensive Nanodegree. Learn sentiment analysis, machine translation, and speech recognition through hands-on projects, guided by industry experts from Fortune 500 companies.
Overview
Syllabus
- Welcome to Natural Language Processing
- This section provides an overview of the program and introduces the fundamentals of Natural Language Processing through symbolic manipulation, including text cleaning, normalization, and tokenization. You'll then build a part of speech tagger using hidden Markov models.
- Introduction to Natural Language Processing
- Start your NLP journey by exploring text cleaning, normalization, tokenization, and spam classification. Then, create a part-of-speech tagger with Hidden Markov Models in an applied project.
- Computing With Natural Language
- Learn advanced NLP methods including word embeddings, topic modeling, sentiment analysis, and attention-based RNNs. Apply these skills to design, train, and implement a machine translation system from start to finish.
- Communicating with Natural Language
- Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.
- Recurrent Neural Networks (NLP Elective)
- Keras
- Sentiment Analysis Extras
- TensorFlow
- Embeddings and Word2Vec
- PyTorch
- Additional Text Preprocessing
Taught by
Luis Serrano, Jay Alammar, Arpan Chakraborty, Dana Sheahen, Daniel C., Mansa kaur k., Shukhrat K., Ammar A., Philippe Claude Alain R. and Dapeng L.
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