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Machine Translation
  • Level Professional
  • المدة 28 ساعات hours
  • الطبع بواسطة Karlsruhe Institute of Technology
  • Offered by

عن

Welcome to the CLICS-Machine Translation MOOC This MOOC explains the basic principles of machine translation. Machine translation is the task of translating from one natural language to another natural language. Therefore, these algorithms can help people communicate in different languages. Such algorithms are used in common applications, from Google Translate to apps on your mobile device. After taking this course you will be able to understand the main difficulties of translating natural languages and the principles of different machine translation approaches. A main focus of the course will be the current state-of-the-art neural machine translation technology which uses deep learning methods to model the translation process. You will be able to decide which concepts fit your machine translation application best. This course is taught by Prof. Dr. Alexander Waibel (http://isl.anthropomatik.kit.edu/english/21_74.php) and Assistant Professor Dr. Jan Niehus (https://www.maastrichtuniversity.nl/jan.niehues).

الوحدات

Introduction

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  • Introduction

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  • Introduction

History

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  • History

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  • History

Approaches

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  • Approaches

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  • Approaches

Applications

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  • Applications

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  • Applications

Course Overview

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  • Introduction

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  • Overview

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  • Additional materials

Language

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    • 1 Discussion
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  • Language

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  • Introduction: Syntax tree

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  • Language

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Difficulties

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  • Difficulties

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  • Incorrect translations

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  • Difficulties

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Approaches

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  • Approaches

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  • Approaches to MT

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Data

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  • Data

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Evaluation

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  • Evaluation

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Human Evaluation

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  • Human Evaluation

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BLEU – Bilingual Evaluation Understudy

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  • BLEU

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Machine Translation Metrics

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  • Machine Translation Metrics

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  • MT Metrics

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Word-based Statistical Machine Translation

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  • Word-based Statistical Machine Translation

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  • Word-based Statistical Machine Translation

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Language Model

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  • Language Model

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  • Language Model

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From Noisy-channel model to Log-linear model

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  • From Noisy-channel model to Log-linear model

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  • From Noisy channel model to Log-linear Model

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Phrase based Machine Translation

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  • Phrase based Machine Translation

Advanced SMT

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  • Advanced SMT

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Introduction to Neural Networks

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  • Introduction to Neural Networks

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  • Introduction to Neutral Networks

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Feed Forward Neural Network Language Model

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  • Feed Forward Neural Network Language Model

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  • Feed Foward Neural Network Language Model

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Recurrent Neural Network Language Model

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  • Recurrent Neural Network Language Model

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  • Reccurent Neural Network Language Model

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Neural Translation Model

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  • Neural Translation Model

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  • Neural Translation Model

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Encoder-Decoder

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  • Encoder-Decoder

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  • Encoder Decoder

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NMT-Training

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  • NMT-Training

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NMT Decoding

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  • NMT Decoding

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Attention based NMT

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  • Attention based NMT

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  • Attention Based NMT

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Combination

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  • Combination

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  • Combination

Vocabulary

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  • Vocabulary

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Monolingual Data

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  • Monolingual Data

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Multilingual

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  • Multilingual

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  • Multilingual Machine Translation

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NMT - Architectures

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  • NMT - Architectures

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Auto Summary

Unlock the world of Machine Translation with this advanced Data Science & AI course on Coursera. Taught by esteemed professors Alexander Waibel and Jan Niehus, the course delves into the intricacies of translating natural languages using state-of-the-art neural machine translation technology. Over 1680 minutes, you'll explore deep learning methods and understand various translation approaches. Ideal for professionals, the course is available with Starter and Professional subscription options. Enhance your skills in a key AI domain today!

Alexander Waibel
Instructors

Alexander Waibel

Jan Niehues
Instructors

Jan Niehues