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Dies ist eine Einführung in die Grundlagen von TensorFlow. Darin werden die Konzepte und APIs erläutert, die Sie zum Schreiben verteilter Modelle für maschinelles Lernen benötigen. Außerdem wird anhand eines TensorFlow-Modells erklärt, wie Sie Modelle in großem Umfang trainieren und mit Cloud Machine Learning Engine effektive Vorhersagen treffen können.
Lernziele:
Modelle für maschinelles Lernen in TensorFlow erstellen
Diverse Herausforderungen mit TensorFlow-Bibliotheken lösen
Gängige Codefehler in TensorFlow beheben
Mit tf.estimator ein ML-Modell erstellen, trainieren und bewerten
ML-Modelle im großen Umfang mit Cloud ML Engine...
Read more
Dies ist eine Einführung in die Grundlagen von TensorFlow. Darin werden die Konzepte und APIs erläutert, die Sie zum Schreiben verteilter Modelle für maschinelles Lernen benötigen. Außerdem wird anhand eines TensorFlow-Modells erklärt, wie Sie Modelle in großem Umfang trainieren und mit Cloud Machine Learning Engine effektive Vorhersagen treffen können.
Lernziele:
Modelle für maschinelles Lernen in TensorFlow erstellen
Diverse Herausforderungen mit TensorFlow-Bibliotheken lösen
Gängige Codefehler in TensorFlow beheben
Mit tf.estimator ein ML-Modell erstellen, trainieren und bewerten
ML-Modelle im großen Umfang mit Cloud ML Engine...
Read more
Dies ist eine Einführung in die Grundlagen von TensorFlow. Darin werden die Konzepte und APIs erläutert, die Sie zum Schreiben verteilter Modelle für maschinelles Lernen benötigen. Außerdem wird anhand eines TensorFlow-Modells erklärt, wie Sie Modelle in großem Umfang trainieren und mit Cloud Machine Learning Engine effektive Vorhersagen treffen können.
Lernziele:
Modelle für maschinelles Lernen in TensorFlow erstellen
Diverse Herausforderungen mit TensorFlow-Bibliotheken lösen
Gängige Codefehler in TensorFlow beheben
Mit tf.estimator ein ML-Modell erstellen, trainieren und bewerten
ML-Modelle im großen Umfang mit Cloud ML Engine trainieren, bereitstellen und in der Produktion verwenden
Register for this course and see more details by visiting:
OpenCourser.com/course/5r7ow8/intro
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on TensorFlow fundamentals, offering a solid basis for understanding TensorFlow concepts
Introduces TensorFlow's distributed machine learning capabilities, addressing challenges in building large-scale models
Leverages Cloud Machine Learning Engine for practical training and deployment of TensorFlow models, enhancing their real-world applicability
Prepares learners to develop, train, and evaluate ML models using the tf.estimator API, a widely adopted TensorFlow tool
Provides hands-on experience in resolving common TensorFlow code errors, ensuring a practical understanding of TensorFlow development
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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 Intro to TensorFlow auf Deutsch with these
activities:
Review Python programming
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Reviewing Python programming will ensure that you have a strong foundation for this course.
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Python
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Review linear algebra
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Reviewing linear algebra will ensure that you have a strong foundation for this course.
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Linear Algebra
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Review the book TensorFlow 2.0 Cookbook
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Reviewing the TensorFlow 2.0 Cookbook will provide you with many examples and solutions to common problems when working with TensorFlow.
Browse courses on
TensorFlow
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Four other activities
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TensorFlow Tutorial
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Following along with the TensorFlow Tutorial is an excellent way to practice the concepts covered in class.
Browse courses on
TensorFlow
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TensorFlow coding exercises
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Completing the TensorFlow coding exercises will provide you with additional practice applying the concepts covered in class.
Browse courses on
TensorFlow
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TensorFlow debugging exercises
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Completing the TensorFlow debugging exercises will provide you with additional practice debugging your own TensorFlow code.
Browse courses on
TensorFlow
Show steps
TensorFlow blog post
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Writing a blog post about TensorFlow will help you to solidify your understanding of the concepts covered in class.
Browse courses on
TensorFlow
Show steps
Review Python programming
Show steps
Reviewing Python programming will ensure that you have a strong foundation for this course.
Browse courses on
Python
Show steps
Show steps
Show steps
Review linear algebra
Show steps
Reviewing linear algebra will ensure that you have a strong foundation for this course.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
Review the book TensorFlow 2.0 Cookbook
Show steps
Reviewing the TensorFlow 2.0 Cookbook will provide you with many examples and solutions to common problems when working with TensorFlow.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
Four other activities
Expand to see all activities and additional details
Show all seven activities
TensorFlow Tutorial
Show steps
Following along with the TensorFlow Tutorial is an excellent way to practice the concepts covered in class.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
TensorFlow coding exercises
Show steps
Completing the TensorFlow coding exercises will provide you with additional practice applying the concepts covered in class.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
TensorFlow debugging exercises
Show steps
Completing the TensorFlow debugging exercises will provide you with additional practice debugging your own TensorFlow code.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
TensorFlow blog post
Show steps
Writing a blog post about TensorFlow will help you to solidify your understanding of the concepts covered in class.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
Career center
Learners who complete Intro to TensorFlow auf Deutsch will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Researcher
Artificial Intelligence Researcher
TensorFlow is one of the most popular frameworks for developing artificial intelligence. This course will introduce you to TensorFlow, which helps build a foundation for success in Artificial Intelligence Research.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
TensorFlow is a leading framework for machine learning and artificial intelligence. This course introduces you to TensorFlow, which helps you build a strong foundation in Artificial Intelligence Engineering.
Machine Learning Scientist
Machine Learning Scientist
TensorFlow is a popular framework for machine learning. As a Machine Learning Scientist, you will need to have a strong understanding of TensorFlow. This course introduces you to TensorFlow, which helps build a foundation for success in Machine Learning Science.
Data Scientist
Data Scientist
Machine learning is becoming an increasingly important tool for Data Scientists. TensorFlow is a popular framework for machine learning. This course helps you start learning about TensorFlow, which may help you become a more effective Data Scientist.
Machine Learning Engineer
Machine Learning Engineer
TensorFlow is one of the most popular frameworks for machine learning today. This course will introduce you to the fundamentals of TensorFlow, which will help you succeed as a Machine Learning Engineer.
Natural Language Processing Engineer
Natural Language Processing Engineer
Machine learning is becoming an essential tool for Natural Language Processing Engineers. This course introduces you to TensorFlow, which helps build a strong foundation in Natural Language Processing Engineering.
Machine Learning Architect
Machine Learning Architect
TensorFlow is one of the most popular frameworks for machine learning. This course will introduce you to TensorFlow, which helps build a foundation for success as a Machine Learning Architect.
Computer Vision Engineer
Computer Vision Engineer
Machine learning is essential to the field of Computer Vision Engineering. TensorFlow is a popular framework for machine learning. This course provides an introduction to TensorFlow, which may be helpful for you as a Computer Vision Engineer.
Computational Scientist
Computational Scientist
Machine learning is becoming more and more important in computational science. This course will introduce you to TensorFlow, which will provide you the foundation you need to become a Computational Scientist.
Robotics Engineer
Robotics Engineer
Machine learning is becoming increasingly important for Robotics Engineers. This course introduces you to TensorFlow, which helps build a foundation for success in Robotics Engineering.
Business Intelligence Analyst
Business Intelligence Analyst
Machine learning is becoming more common in Business Intelligence Analysis. TensorFlow is a popular framework for machine learning. This course can be a useful introduction to TensorFlow if you wish to be a Business Intelligence Analyst.
Data Analyst
Data Analyst
Machine learning is an important skill set for any Data Analyst and TensorFlow is a popular framework for machine learning. This course introduces you to the fundamentals of TensorFlow, which may prove useful for working as a Data Analyst.
Data Science Manager
Data Science Manager
Machine learning is a key component of a Data Science Manager's work. TensorFlow is a popular framework for machine learning. This course helps you start learning about TensorFlow, which may help you build a foundation for success in Data Science Management.
Data Engineer
Data Engineer
Machine learning is becoming increasingly important for Data Engineers. This course will introduce you to TensorFlow, which may prove useful to your career as a Data Engineer.
Software Engineer
Software Engineer
TensorFlow is a popular framework for machine learning. Machine learning is becoming a key skill for Software Engineers to have. This course will introduce you to TensorFlow, which may help you become a more well-rounded Software Engineer.
For more career information including salaries, visit:
OpenCourser.com/course/5r7ow8/intro
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
Intro to TensorFlow auf Deutsch.
A comprehensive guide to deep learning, with a focus on Python and TensorFlow. Suitable for intermediate to advanced learners.
An end-to-end machine learning platform built on TensorFlow, suitable for advanced learners.
Covers a wide range of machine learning algorithms and techniques, using TensorFlow 2.0. Suitable for intermediate learners.
Provides a comprehensive guide to machine learning using Python. It's a good resource for additional context and examples.
Is written from the perspective of a data scientist and provides practical examples of how to use TensorFlow to solve common data analysis problems.
A lightweight version of TensorFlow for mobile and embedded devices, suitable for intermediate to advanced learners.
Provides a comprehensive introduction to deep learning using Python and Keras. After the course, this book can provide additional insights into deep learning concepts.
Practical guide to using TensorFlow. It provides a set of recipes and code examples that demonstrate how to solve common machine learning problems using TensorFlow.
Provides a visual and intuitive introduction to deep learning. It's a good resource for understanding the underlying concepts.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5r7ow8/intro
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Time
9 hours
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
This course belongs to a
collection
called
Machine Learning with TensorFlow on Google Cloud Platform auf Deutsch. It's comprised of five courses:
- Launching into Machine Learning auf Deutsch
- Feature Engineering auf Deutsch
- Art and Science of Machine Learning auf Deutsch
- How Google does Machine Learning auf Deutsch
- Intro to TensorFlow auf Deutsch (viewing)
Good to know
Focuses on TensorFlow fundamentals, offering a solid basis for understanding TensorFlow concepts
Introduces TensorFlow's distributed machine learning capabilities, addressing challenges in building large-scale models
Leverages Cloud Machine Learning Engine for practical training and deployment of TensorFlow models, enhancing their real-world applicability
Prepares learners to develop, train, and evaluate ML models using the tf.estimator API, a widely adopted TensorFlow tool
Provides hands-on experience in resolving common TensorFlow code errors, ensuring a practical understanding of TensorFlow development
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