Natural Language Processing with Sequence Models
In Course 3 of the Natural Language Processing Specialization, you will:a) Train a neural network with GLoVe word embeddings to perform sentiment analysis of tweets,
b) Generate synthetic Shakespeare text using a Gated Recurrent Unit (GRU) language model,
c) Train a recurrent neural network to perform named entity recognition (NER) using LSTMs with linear layers, and
d) Use so-called ‘Siamese’ LSTM models to compare questions in a corpus and identify those that are worded differently but have the same meaning.
By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot!
This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.
Use recurrent neural networks, LSTMs, GRUs & Siamese networks in Trax for sentiment analysis, text generation & named entity recognition.
Syllabus
Syllabus - What you will learn from this course
Week 1
Neural Networks for Sentiment Analysis
Week 2
Recurrent Neural Networks for Language Modeling
Week 3
LSTMs and Named Entity Recognition
Week 4
Siamese Networks
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
Absolutely satisfied with the tons of things I learnt. Professor Jounes and his team did a great work. Looking forward to enrolling to next course.
Excellent slides, notebooks, assignments, course content, conciseness, explanations. All great. Made all the topics very accessible.
It's a great introduction to the Trax Framework for Deep Learning. Building cool models for NLP makes the course well worth it.
Great information, but some of the assignments had errors and there weren't many interactions from the TAs on the Slack or Forum
