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Attention Mechanism with Google Cloud

Google Cloud Training

Take Udacity's free Cloud Attention Mechanism Course by Google and learn how attention works, and how it can be used to improve the performance of a variety of machine learning.

Prerequisite details

Take Udacity's free Cloud Attention Mechanism Course by Google and learn how attention works, and how it can be used to improve the performance of a variety of machine learning.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

NLP proficiency
Computer vision proficiency
Intermediate Python
Basic machine learning

You will also need to be able to communicate fluently and professionally in written and spoken English.

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What's inside

Syllabus

This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a comprehensive overview of the attention mechanism in machine learning

Suitable for individuals with prior knowledge of NLP, computer vision, intermediate Python, and basic machine learning

Meets industry standards for machine learning practices

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Activities

Coming soon We're preparing activities for Attention Mechanism with Google Cloud. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Attention Mechanism with Google Cloud will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Engineer

As a Natural Language Processing Engineer, you will be working with text and language data. Attention mechanisms are a powerful tool for understanding the meaning of text, and can be used to develop applications such as machine translation, text summarization, and question answering. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Natural Language Processing Engineer.

See salaries and explore the career path for Natural Language Processing Engineer

Computer Vision Engineer

As a Computer Vision Engineer, you will be working with images and videos. Attention mechanisms are a powerful tool for understanding the content of images and videos, and can be used to develop applications such as object detection, image classification, and video analysis. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Computer Vision Engineer.

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Researcher

As a Researcher, you will be conducting research in a variety of fields, including machine learning, natural language processing, and computer vision. Attention mechanisms are a powerful tool for understanding complex problems, and can be used to develop new and innovative solutions. This course will provide you with the skills needed to use attention mechanisms effectively in your own research, and will help you to become a more effective Researcher.

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Machine Learning Engineer

As a Machine Learning Engineer, you will be tasked with developing and implementing machine learning models to solve a variety of problems. Attention mechanisms are a powerful technique that can be used to improve the performance of machine learning models, and can be particularly useful for tasks such as natural language processing and computer vision. This course will provide you with a solid foundation in attention mechanisms, and will help you to develop the skills needed to use them effectively in your own work.

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Data Scientist

As a Data Scientist, you will be using data to make informed decisions. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Data Scientist.

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Data Engineer

As a Data Engineer, you will be building and maintaining data pipelines and infrastructure. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to develop data pipelines that are more efficient and accurate. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Data Engineer.

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Product Manager

As a Product Manager, you will be responsible for developing and managing products. Attention mechanisms are a powerful tool for understanding the needs of users, and can be used to develop products that are more useful, engaging, and user-friendly. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Product Manager.

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Risk Analyst

As a Risk Analyst, you will be using data to identify and assess risks. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Risk Analyst.

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Quantitative Analyst

As a Quantitative Analyst, you will be using mathematical and statistical models to make informed decisions about financial investments. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Quantitative Analyst.

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Actuary

As an Actuary, you will be using mathematical and statistical models to assess risks and make informed decisions about insurance policies. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Actuary.

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Software Engineer

As a Software Engineer, you will be designing, developing, and maintaining software applications. Attention mechanisms are a powerful tool for improving the performance of software applications, and can be used to develop applications that are more efficient, accurate, and user-friendly. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Software Engineer.

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Statistician

As a Statistician, you will be using mathematical and statistical models to analyze data and make informed decisions. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Statistician.

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Data Analyst

As a Data Analyst, you will be using data to make informed decisions. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

As a Business Analyst, you will be using data to make informed decisions about business operations. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Business Analyst.

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Financial Analyst

As a Financial Analyst, you will be using data to make informed decisions about financial investments. Attention mechanisms are a powerful tool for understanding the relationships between different pieces of data, and can be used to identify patterns and trends that would be difficult to see with traditional methods. This course will provide you with the skills needed to use attention mechanisms effectively in your own work, and will help you to become a more effective Financial Analyst.

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Reading list

We've selected four books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Attention Mechanism with Google Cloud.

Cross-Lingual Word Embeddings

Save

Provides a comprehensive introduction to deep learning for natural language processing, and covers topics such as word embeddings, recurrent neural networks, transformers, and attention mechanisms. It is suitable for beginners with little to no prior knowledge in NLP.

Cross-Lingual Word Embeddings (Synthesis Lectures...

Paperback

Natural Language Processing with PyTorch

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Provides a comprehensive introduction to natural language processing using PyTorch, and covers topics such as tokenization, embedding, attention mechanisms, and sequence transduction models. It is suitable for beginners with little to no prior knowledge in NLP and PyTorch.

Natural Language Processing with PyTorch: Build...

Paperback

$$$

(Deutsch) Natural Language Processing mit PyTorch:...

Kindle Edition

(中文) Based on natural language processing...

Paperback

Deep Learning with Python, Second Edition

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Provides a practical introduction to deep learning using Python and the Keras API. It covers topics such as neural networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks. It is suitable for beginners with little to no prior knowledge in deep learning.

Deep Learning with Python, Second Edition

Paperback

Deep Learning with Python, Second Edition

Kindle Edition

Computer Vision

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Provides a comprehensive introduction to computer vision, and covers topics such as image formation, image processing, feature detection, object recognition, and video analysis. It is suitable for beginners with little to no prior knowledge in computer vision.

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Effort

45 minutes

Via

Udacity

Instructor

Google Cloud Training

Language

English

Good to know

Provides a comprehensive overview of the attention mechanism in machine learning

Suitable for individuals with prior knowledge of NLP, computer vision, intermediate Python, and basic machine learning

Meets industry standards for machine learning practices

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