This course, part of the Natural Language Processing Specialization, includes three modules focused on practical NLP applications. You'll learn to train neural networks with GLoVe embeddings for sentiment analysis of tweets, generate synthetic Shakespeare text using GRU language models, and perform named entity recognition with LSTMs.
Additionally, you'll use 'Siamese' LSTM models to identify similarly worded questions. By the end of the course, you'll have designed NLP tools for question-answering, sentiment analysis, language translation, text summarization, and built a chatbot.
🆓 Free to Audit
🕒 Approx. 21 Hours
✏️ Intermediate Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by DeepLearning.AI via Coursera
