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Transformer Models and BERT Model with Google Cloud
Google Cloud Training
Google Cloud Training
Take Udacity's free Cloud Transformer Models and BERT Course by Google and learn about the main components of the Transformer architecture and how it is used to build the BERT model.
Prerequisite details
Read more
Take Udacity's free Cloud Transformer Models and BERT Course by Google and learn about the main components of the Transformer architecture and how it is used to build the BERT model.
Prerequisite details
Read more
Take Udacity's free Cloud Transformer Models and BERT Course by Google and learn about the main components of the Transformer architecture and how it is used to build the BERT model.
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:
- Machine learning model implementation
- TensorFlow
- Machine learning frameworks in Python
- Intermediate Python
- Attention mechanisms
- PyTorch
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/c2x4xz/transformer
What's inside
Syllabus
This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds a strong foundation for learners with no prior machine learning experience
Teaches the latest deep learning architectures used in industry
Taught by Google Cloud Training, a recognized expert in the field
Introduces Transformer architecture, which is foundational for many deep learning applications
Prerequisite knowledge required: ML model implementation, TensorFlow, Python, attention mechanisms
Good fluency in English is required
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Save Transformer Models and BERT Model with Google Cloud to your list so you can find it easily later:
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Activities
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We're preparing activities for
Transformer Models and BERT Model with Google Cloud.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Transformer Models and BERT Model with Google Cloud will develop knowledge and skills
that may be useful to these careers:
Deep Learning Architect
Deep Learning Architect
Deep Learning Architects design and develop deep learning systems for complex problems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Deep Learning Architects who want to learn more about the Transformer architecture and the BERT model.
Deep Learning Engineer
Deep Learning Engineer
Deep Learning Engineers design, develop, and maintain deep learning models. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Deep Learning Engineers who want to learn more about the Transformer architecture and the BERT model.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and models to solve real-world problems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Machine Learning Researchers who want to learn more about the Transformer architecture and the BERT model.
Machine Learning Architect
Machine Learning Architect
Machine Learning Architects design and develop machine learning systems for complex problems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Machine Learning Architects who want to learn more about the Transformer architecture and the BERT model.
Natural Language Processing Researcher
Natural Language Processing Researcher
Natural Language Processing Researchers develop new natural language processing algorithms and models to understand and generate human language. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Natural Language Processing Researchers who want to learn more about the Transformer architecture and the BERT model.
Natural Language Understanding Engineer
Natural Language Understanding Engineer
Natural Language Understanding Engineers design, develop, and maintain natural language understanding systems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Natural Language Understanding Engineers who want to learn more about the Transformer architecture and the BERT model.
Speech Recognition Engineer
Speech Recognition Engineer
Speech Recognition Engineers design, develop, and maintain speech recognition systems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Speech Recognition Engineers who want to learn more about the Transformer architecture and the BERT model.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design, develop, and maintain computer vision systems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Computer Vision Engineers who want to learn more about the Transformer architecture and the BERT model.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and maintain artificial intelligence systems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Artificial Intelligence Engineers who want to learn more about the Transformer architecture and the BERT model.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers design, develop, and maintain software systems that can understand and generate human language. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Natural Language Processing Engineers who want to learn more about the Transformer architecture and the BERT model.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers research, design, develop, and deploy machine learning algorithms and models to solve real-world problems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Machine Learning Engineers who want to learn more about the Transformer architecture and the BERT model.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Software Engineers who want to learn more about the Transformer architecture and the BERT model.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They work in a variety of industries, including finance, healthcare, manufacturing, and transportation. This course may be useful to Data Analysts who want to learn more about the Transformer architecture and the BERT model.
Research Scientist
Research Scientist
Research Scientists conduct research in a variety of scientific fields, including computer science, physics, biology, and chemistry. This course may be useful to Research Scientists who want to learn more about the Transformer architecture and the BERT model.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful to Data Scientists who want to learn more about the Transformer architecture and the BERT model.
For more career information including salaries, visit:
OpenCourser.com/course/c2x4xz/transformer
Reading list
We've selected nine 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
Transformer Models and BERT Model with Google Cloud.
Provides a comprehensive overview of Bayesian reasoning and machine learning. It valuable resource for those who want to learn more about the theory and practice of Bayesian reasoning and machine learning.
Provides a comprehensive overview of deep learning techniques for natural language processing. It valuable resource for those who want to learn more about the theory and practice of deep learning models for natural language processing.
Provides a comprehensive overview of natural language processing techniques in Python. It valuable resource for those who want to learn more about the theory and practice of natural language processing.
Provides a comprehensive overview of speech and language processing. It valuable resource for those who want to learn more about the theory and practice of speech and language processing.
Save
Provides a comprehensive overview of machine learning concepts and techniques. It valuable resource for those who want to learn more about the theory and practice of machine learning.
Save
Provides a comprehensive overview of deep learning concepts and techniques. It valuable resource for those who want to learn more about the theory and practice of deep learning.
Provides a comprehensive overview of reinforcement learning concepts and techniques. It valuable resource for those who want to learn more about the theory and practice of reinforcement learning.
Provides a comprehensive overview of probabilistic graphical models. It valuable resource for those who want to learn more about the theory and practice of probabilistic graphical models.
Provides a practical introduction to natural language processing. It valuable resource for those who want to learn more about the theory and practice of natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/c2x4xz/transformer
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Effort
45 minutes
Via
Udacity
Instructor
Google Cloud Training
Language
English
Good to know
Builds a strong foundation for learners with no prior machine learning experience
Teaches the latest deep learning architectures used in industry
Taught by Google Cloud Training, a recognized expert in the field
Introduces Transformer architecture, which is foundational for many deep learning applications
Prerequisite knowledge required: ML model implementation, TensorFlow, Python, attention mechanisms
Good fluency in English is required
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