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Natural Language Processing in TensorFlow Coursera

Highlights
Tuition fee
Free
Free
Free
Unknown
Tuition fee
Free
Free
Free
Unknown
Duration
14 days
Duration
14 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
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Taught in
English
Taught in
English

About

This Natural Language Processing in TensorFlow course offered by Coursera in partnership with Deeplearning will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Overview

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. 

In Natural Language Processing in TensorFlow course offered by Coursera in partnership with Deeplearning 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!

Key facts

  • 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.

Programme Structure

Courses include:

  • Sentiment in text
  • Word Embeddings
  • Sequence models
  • Sequence models and literature

Key information

Duration

  • Part-time
    • 14 days
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Intermediate Level

  • You should take the first 2 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • Audit: free access to course materials except graded items
  • Certificate: a trusted way to showcase your skills
  • A year of unlimited access with Coursera Plus $199

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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