Natural Language Processing in TensorFlow

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.In this four-course Specialization, you'll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network's performance using convolutions as you train it to identify real-world images. You'll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input

( 165 Reviews )

Created by: Laurence Moroney

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Overall Score : 86 / 100

Course Description

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.In Course 3 of the deeplearning.ai TensorFlow Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network. You'll also learn to apply RNNs, GRUs, and LSTMs in TensorFlow. Finally, you'll get to train an LSTM on existing text to create original poetry!The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

Time: 9h

Instructor Details

Laurence Moroney

4.3 Rating
165 Reviews

Laurence Moroney is a Developer Advocate at Google working on Artificial Intelligence with TensorFlow. As the author of more programming books than he can count, he's excited to be working with deeplearn.ai and Coursera in producing video training. When not working with technology, he's a member of the Science Fiction Writers of America, having authored several science fiction novels, a produced screenplay and comic books, including the prequel to the movie 'Equilibrium' starring Christian Bale. Laurence is based in Washington State, where he drinks way too much coffee.

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By Mejzo on 16-Nov-19

Giving feed back so it may trigger some evaluation on this course. The course is very weak. Lacks material and engagement feeling. I would say increase the aterial 800-1000 percent , add homeworks, etc..

By Benniah S D S on 27-Aug-19

Really good!But slightly shallow.

By Hasitha K on 28-Aug-19

As usual, stage set for introduction, Great examples, Practical workshop, and quiz.

By Ranju M on 27-Aug-19

Excellent. Isn't Laurence just great! Fantastically deep knowledge, easy learning style, very practical presentation. And funny! A pure joy, highly relevant and extremely useful of course. Thank you!

By Amrita G on 10-Oct-19

A Great Intuitive approach towards NLP for direct dive into real-time projects.

By Vikas A on 6-Oct-19

Very nice course! Suggest for everyone.

By Muhammad S Z on 7-Oct-19

Nice intro to NLP, good examples. I like the way course is divided to small pieces which separately can be easily digested

By Sharmila K on 3-Oct-19

It looks a bit simple

By Ajith K on 3-Oct-19

Excellent introductory course on NLP, the Tensorflow examples are clear and simple to follow, recommended for anyone looking for a quick NLP summary course

By Jatin J on 1-Oct-19

Very nice combination of theory on the one side and coding on the other. Everything was explained in a crystal clear fashion.

By Raja D on 7-Sep-19

very user friendly approach, and notes. good simplified explanation of steps by Mr.Laurence.

By Petrescu A R on 28-Aug-19

very useful and helpful courses on NLP, it gives intuitive and first-hand directions on how to use RNN models, the teacher is really wonderful, thank you!