Natural Language Processing with Attention Models
Learn NLP in Course 4 of the Natural Language Processing Specialization. Translate, summarize, and build chatbots using advanced models like Transformer, T5, and BERT. Gain expertise in machine learning, Python, calculus, linear algebra, and statistics. Taught by NLP experts from Stanford University and Google Brain.
In Course 4 of the Natural Language Processing Specialization, you will:
a) Translate complete English sentences into German using an encoder-decoder attention model,
b) Build a Transformer model to summarize text,
c) Use T5 and BERT models to perform question-answering, and
d) Build a chatbot using a Reformer model.
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!
Learners should have a working knowledge of machine learning, intermediate Python including experience with a deep learning framework (e.g., TensorFlow, Keras), as well as proficiency in calculus, linear algebra, and statistics. Please make sure that you’ve completed course 3 – Natural Language Processing with Sequence Models – before starting this course.
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.
User Reviews
Be the first to review “Natural Language Processing with Attention Models”
You must be logged in to post a review.
There are no reviews yet.