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Machine Translation in Python

Are you curious about the inner workings of the models that are behind products like Google Translate?

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4 Hours16 Videos58 Exercises2,622 Learners
4950 XP

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Course Description

The need to pack a bilingual dictionary for your European holiday or keeping one on your desk to complete your foreign language homework is a thing of the past. You just hop on the internet and make use of a language translation service to quickly understand what the street sign means or finding out how to greet and thank a foreigner in their language. Behind the language translation services are complex machine translation models. Have you ever wondered how these models work? This course will allow you to explore the inner workings of a machine translation model. You will use Keras, a powerful Python-based deep learning library, to implement a translation model. You will then train the model to perform an English to French translation, and you will be shown techniques to improve your model. At the end of this course, you would have developed an in-depth understanding of machine translation models and appreciate them even more!

  1. 1

    Introduction to machine translation


    In this chapter, you'll understand what the encoder-decoder architecture is and how it is used for machine translation. You will also learn about Gated Recurrent Units (GRUs) and how they are used in the encoder-decoder architecture.

    Play Chapter Now
    Introduction to machine translation
    50 xp
    Understanding one-hot vectors
    100 xp
    Part 1: Exploring the to_categorical() function
    100 xp
    Part 2: Exploring the to_categorical() function
    100 xp
    Encoder decoder architecture
    50 xp
    Part 1: Text reversing model - Encoder
    100 xp
    Part 2: Text reversing model - Encoder
    100 xp
    Complete text reversing model
    100 xp
    Understanding sequential models
    50 xp
    Part 1: Understanding GRU models
    100 xp
    Part 2: Understanding GRU models
    100 xp
    Understanding sequential model output
    100 xp

In the following tracks

Deep Learning for NLP


Ruanne Van Der WaltMona Khalil
Thushan Ganegedara Headshot

Thushan Ganegedara

Data Scientist and Author

Thushan Ganegedara is a Senior Data Scientist. He is the author of TF2 in Action - Manning and NLP with TensorFlow (v1.6). He has over 4 years experience with TensorFlow. Thushan likes to wear many hats as a YouTuber, blogger, presenter and a StackOverflow contributor. Deep learning and machine learning stand out as his passions. Unless he's dwelling in latest ML research you can find him meditating or swimming (not at the same time). Follow him on LinkedIn.
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