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Attention Mechanism: Enhancing Neural Networks

Learn how attention mechanisms improve machine learning tasks like translation and text summarization in just one hour.

Learn how attention mechanisms improve machine learning tasks like translation and text summarization in just one hour.

This course introduces the attention mechanism, an effective technique that allows neural networks to focus on specific parts of an input sequence. You'll discover how attention works and how to use it to improve performance in various machine learning tasks, including machine translation, text summarization, and question answering. The course provides a concise yet comprehensive overview of this powerful concept, enabling intermediate-level learners to understand and potentially apply attention mechanisms in their own projects.

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Attention Mechanism: Enhancing Neural Networks

This course includes

1 Hour

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,435

What you'll learn

  • Understand the concept of attention and how it works

  • Learn how the attention mechanism applies to machine translation

  • Explore applications of attention in text summarization

  • Discover the role of attention in question-answering systems

  • Grasp the implementation of attention in neural network architectures

  • Understand the advantages of attention over traditional sequence models

Skills you'll gain

attention mechanism
neural networks
machine translation
text summarization
sequence modeling

This course includes:

4 Minutes PreRecorded video

1 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There is 1 module in this course

This course provides an introduction to the attention mechanism, a powerful technique used in modern neural networks. Participants will learn how attention allows models to focus on specific parts of input sequences, greatly improving performance in various machine learning tasks. The course covers the fundamental concepts of attention, its implementation in neural architectures, and its applications in areas such as machine translation, text summarization, and question answering. By the end of this concise one-hour course, learners will understand how attention mechanisms work and how they can be applied to enhance the capabilities of neural networks in processing sequential data.

Présentation du mécanisme d'attention

Module 1 · 18 Minutes to complete

Fee Structure

Payment options

Financial Aid

Instructor

Google Cloud Training
Google Cloud Training

4.7 rating

86 Reviews

26,85,892 Students

1,554 Courses

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The Google Cloud Training team is tasked with developing, delivering, and evaluating training programs that enable our enterprise customers and partners to effectively utilize our products and solutions. Google Cloud empowers millions of organizations to enhance employee capabilities, improve customer service, and innovate for the future using cutting-edge technology built specifically for the cloud. Our products are designed with a focus on security, reliability, and scalability, covering everything from infrastructure to applications, devices, and hardware. Our dedicated teams are committed to helping customers successfully leverage our technologies to drive their success.

Attention Mechanism: Enhancing Neural Networks

This course includes

1 Hour

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,435

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.