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本課程概要說明解碼器與編碼器的架構,這種強大且常見的機器學習架構適用於序列對序列的任務,例如機器翻譯、文字摘要和回答問題。您將認識編碼器與解碼器架構的主要元件,並瞭解如何訓練及提供這些模型。在對應的研究室逐步操作說明中,您將學習如何從頭開始使用 TensorFlow 寫程式,導入簡單的編碼器與解碼器架構來產生詩詞。

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What's inside

Syllabus

解碼器與編碼器的架構:總覽
本單元概要說明解碼器與編碼器的架構,這種強大且常見的機器學習架構適用於序列對序列的任務,例如機器翻譯、文字摘要和回答問題。您將認識編碼器與解碼器架構的主要元件,並瞭解如何訓練及提供這些模型。在對應的研究室逐步操作說明中,您將學習如何從頭開始使用 TensorFlow 寫程式,導入簡單的編碼器與解碼器架構來產生詩詞。

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills for text translation, summarization, and question answering, which are core skills for data scientists
Explores a highly relevant topic in the field of Natural Language Processing
Taught by Google Cloud Training, who are recognized for their industry-leading expertise
Uses Tensorflow, a popular and widely-used framework in the industry
Requires some programming knowledge and experience with Tensorflow
May not be suitable for complete beginners in machine learning

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Encoder-Decoder Architecture - 繁體中文 with these activities:
使用 TensorFlow 构建简单的解碼器与編碼器模型
通过实践练习,巩固对解碼器与編碼器架构的理解,并学习如何使用 TensorFlow 构建这些模型。
Browse courses on TensorFlow
Show steps
  • 寻找有关使用 TensorFlow 构建解碼器与編碼器模型的教程。
  • 逐步完成教程,并尝试不同的超参数。
  • 修改模型以生成自己的文本或序列。
Show all one activities

Career center

Learners who complete Encoder-Decoder Architecture - 繁體中文 will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers are responsible for designing and building the machine learning models that power many of today's most innovative products and services. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field.
Data Scientist
Data Scientists use machine learning and other statistical techniques to extract insights from data. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field.
Software Engineer
Software Engineers design, build, and maintain software applications. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field, especially those interested in working on machine learning projects.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field.
Natural Language Processing Engineer
Natural Language Processing Engineers design and build systems that can understand and generate human language. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field.
Research Scientist
Research Scientists conduct research in a variety of fields, including machine learning, artificial intelligence, and natural language processing. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field.
Artificial Intelligence Engineer
Artificial Intelligence Engineers design and build systems that can perform tasks that typically require human intelligence. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field.
Data Analyst
Data Analysts use data to solve business problems. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge will be essential for anyone looking to enter or advance in this field, especially those interested in working on machine learning projects.
Business Analyst
Business Analysts use data and analytical techniques to improve business processes. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in working on data-driven projects.
Product Manager
Product Managers are responsible for managing the development and launch of new products. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in working on machine learning-powered products.
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing strategies. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in using machine learning to improve marketing campaigns.
Salesforce Administrator
Salesforce Administrators manage and maintain Salesforce systems. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in using machine learning to improve Salesforce implementations.
IT Project Manager
IT Project Managers plan and execute IT projects. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in managing machine learning projects.
Cybersecurity Analyst
Cybersecurity Analysts protect computer systems and networks from cyberattacks. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in using machine learning to improve cybersecurity.
Financial Analyst
Financial Analysts provide financial advice to individuals and businesses. This course provides a solid foundation in the fundamentals of machine learning, including the theory behind encoder-decoder architectures. This knowledge may be helpful for anyone looking to enter or advance in this field, especially those interested in using machine learning to improve financial modeling.

Reading list

We've selected 14 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 Encoder-Decoder Architecture - 繁體中文.
這本書是深度學習的經典著作,深入淺出地介紹了深度學習的基本原理和演算法,對於理解編碼器和解碼器的架構很有幫助。
Classic textbook on speech and language processing, covering a wide range of topics including encoder-decoder architectures for speech recognition and language modeling.
Comprehensive overview of sequence to sequence learning, including a detailed discussion of encoder-decoder architectures.
Provides a practical introduction to natural language processing using PyTorch, with a focus on encoder-decoder architectures for machine translation and question answering.
Provides a comprehensive overview of neural machine translation, including a detailed discussion of encoder-decoder architectures.
Provides a comprehensive overview of computer vision, including a discussion of encoder-decoder architectures for image segmentation and object recognition.
Provides a practical introduction to machine learning, with a focus on the practical aspects of training and deploying models.

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