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Designing Data Pipelines with TensorFlow 2.0
Chase DeHan
Chase DeHan
This course will evaluate one of the largest changes from TensorFlow 1.0 to TensorFlow 2.0 – the tf.data module. This simplified and unified interface makes managing data pipelines easier with tf.data.
Read more
This course will evaluate one of the largest changes from TensorFlow 1.0 to TensorFlow 2.0 – the tf.data module. This simplified and unified interface makes managing data pipelines easier with tf.data.
Read more
This course will evaluate one of the largest changes from TensorFlow 1.0 to TensorFlow 2.0 – the tf.data module. This simplified and unified interface makes managing data pipelines easier with tf.data.
TensorFlow 2.0 has made it easier to manage data pipelines with tf.data through their simplified and unified interface. In this course, Designing Data Pipelines with TensorFlow 2.0, you’ll learn to leverage the performance improvements from the TensorFlow data module. First, you’ll discover how to load data into TensorFlow. Next, you’ll explore prepping data for model training and feature engineering. Finally, you’ll learn how to leverage the performance optimizations of the data pipeline. When you’re finished with this course, you’ll have the skills and knowledge of building data pipelines needed to have data ready for model training in TensorFlow.
Register for this course and see more details by visiting:
OpenCourser.com/course/nzrghp/designing
What's inside
Syllabus
Course Overview
Evaluating TensorFlow Capabilities
Loading Data in TensorFlow
Prepping Data
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Syllabus
Course Overview
Evaluating TensorFlow Capabilities
Loading Data in TensorFlow
Prepping Data
Read more
Optimizing Performance of Pipelines
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops data pipelines using TensorFlow, relevant for practitioners utilizing TensorFlow for deep learning applications
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Career center
Learners who complete Designing Data Pipelines with TensorFlow 2.0 will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers build, test, and maintain data pipelines to ensure data is properly managed and accessible within data architectures. The course, Designing Data Pipelines with TensorFlow 2.0, teaches how to design and develop data pipelines. This course will be particularly helpful for Data Engineers who want to work in a TensorFlow-based environment. It teaches how to load, prep, and optimize data pipelines.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, test, and maintain machine learning models. The course, Designing Data Pipelines with TensorFlow 2.0, can help Machine Learning Engineers learn how to prepare data for training machine learning models. This course will be particularly helpful for Machine Learning Engineers who want to use TensorFlow for machine learning tasks.
Data Scientist
Data Scientist
Data Scientists combine programming skills, math, statistics, and machine learning to extract meaningful insights from data. The course, Designing Data Pipelines with TensorFlow 2.0, can help Data Scientists learn how to prepare data for training models. This course will be particularly helpful for Data Scientists who want to use TensorFlow for machine learning tasks.
Software Engineer
Software Engineer
Software Engineers design, develop, test, and maintain software systems. The course, Designing Data Pipelines with TensorFlow 2.0, can help Software Engineers learn how to build data pipelines for machine learning applications. This course will be particularly helpful for Software Engineers who want to work on machine learning projects.
Data Analyst
Data Analyst
Data Analysts analyze data to extract meaningful insights and communicate those insights to stakeholders. The course, Designing Data Pipelines with TensorFlow 2.0, can help Data Analysts learn how to prepare data for analysis. This course will be particularly helpful for Data Analysts who want to use TensorFlow for data analysis tasks.
DevOps Engineer
DevOps Engineer
DevOps Engineers ensure that software systems are developed and deployed smoothly. The course, Designing Data Pipelines with TensorFlow 2.0, can help DevOps Engineers learn how to build and maintain data pipelines for machine learning applications. This course will be particularly helpful for DevOps Engineers who want to work on machine learning projects.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing systems. The course, Designing Data Pipelines with TensorFlow 2.0, can help Cloud Architects learn how to build data pipelines for machine learning applications in the cloud. This course will be particularly helpful for Cloud Architects who want to work on machine learning projects in the cloud.
Business Analyst
Business Analyst
Business Analysts analyze business needs and develop solutions to meet those needs. The course, Designing Data Pipelines with TensorFlow 2.0, can help Business Analysts learn how to use data to make better decisions. This course will be particularly helpful for Business Analysts who want to work on data-driven projects.
Product Manager
Product Manager
Product Managers develop and manage products. The course, Designing Data Pipelines with TensorFlow 2.0, can help Product Managers learn how to use data to make better decisions about product development. This course will be particularly helpful for Product Managers who want to work on data-driven products.
Technical Writer
Technical Writer
Technical Writers create documentation for software and hardware products. The course, Designing Data Pipelines with TensorFlow 2.0, can help Technical Writers learn how to write documentation for data pipelines. This course will be particularly helpful for Technical Writers who want to work on machine learning projects.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. The course, Designing Data Pipelines with TensorFlow 2.0, can help Statisticians learn how to prepare data for analysis. This course will be particularly helpful for Statisticians who want to use TensorFlow for data analysis tasks.
Data Science Manager
Data Science Manager
Data Science Managers lead teams of data scientists and analysts. The course, Designing Data Pipelines with TensorFlow 2.0, can help Data Science Managers learn how to build and manage data pipelines for machine learning applications. This course will be particularly helpful for Data Science Managers who want to work on machine learning projects.
Research Scientist
Research Scientist
Research Scientists conduct research in various scientific fields. The course, Designing Data Pipelines with TensorFlow 2.0, can help Research Scientists learn how to prepare data for analysis. This course will be particularly helpful for Research Scientists who want to use TensorFlow for machine learning tasks.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. The course, Designing Data Pipelines with TensorFlow 2.0, may be helpful for Quantitative Analysts who want to learn how to use TensorFlow for financial data analysis.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. The course, Designing Data Pipelines with TensorFlow 2.0, may be helpful for Financial Analysts who want to learn how to use TensorFlow for financial data analysis.
For more career information including salaries, visit:
OpenCourser.com/course/nzrghp/designing
Reading list
We've selected ten 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
Designing Data Pipelines with TensorFlow 2.0.
Provides a comprehensive overview of data pipelines in TensorFlow 2.0, with practical examples and real-world use cases.
This guide valuable reference for both beginners and experienced TensorFlow users, covering essential concepts, installation instructions, and practical examples.
This classic textbook offers a comprehensive overview of statistical learning, providing a theoretical foundation for data analysis and machine learning pipelines.
This classic book provides a comprehensive overview of data-intensive applications and their design principles, offering a theoretical foundation for building data pipelines.
Provides a comprehensive overview of machine learning pipelines, covering data preparation, model training, and evaluation, applicable to TensorFlow pipelines.
This cookbook offers practical recipes for common data science tasks, leveraging TensorFlow's capabilities.
Offers a practical introduction to data science with a focus on business applications, providing context for building data pipelines in a real-world setting.
This concise reference guide provides quick access to key concepts and commands for building data pipelines in various technologies, including TensorFlow.
While this book focuses on Apache Beam, it provides valuable insights into data pipelines and can complement the TensorFlow-centric approach of the course.
Provides a gentle introduction to machine learning concepts, making it a useful resource for beginners looking to gain a foundation before diving deeper into data pipelines.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/nzrghp/designing
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Time
113 hours
Level
Intermediate
Via
Pluralsight
Instructor
Chase DeHan
Language
English
Good to know
Develops data pipelines using TensorFlow, relevant for practitioners utilizing TensorFlow for deep learning applications
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