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Authored by Google Cloud
In this course, we will dive into the components and best practices of a high-performing ML system in production environments.
Register for this course and see more details by visiting:
OpenCourser.com/course/u3thsq/production
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Taught by Google Cloud experts, recognized for their innovation in ML
Suitable for professionals wanting to build a high performing machine learning system for production
Delves into best practices for ML systems in production environments
Requires prior knowledge in ML and experience in production environments
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Production Machine Learning Systems.
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Career center
Learners who complete Production Machine Learning Systems will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists explore, analyze, and interpret data to extract insights and trends. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, maintain, and develop solutions that leverage machine learning. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers' responsibilities include designing, building, and testing ML models. This course may be helpful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Software Engineer
Software Engineer
A Software Engineer who focuses on deploying ML models may find this course useful in understanding the components of a high-performing ML system that can be deployed to production environments.
Data Analyst
Data Analyst
Data Analysts explore, analyze, and interpret data to extract insights and trends. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Data Engineer
Data Engineer
Data Engineers are responsible for designing and maintaining the systems and processes that manage data. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Business Analyst
Business Analyst
Business Analysts apply advanced knowledge of business processes and strategies to solve problems within an organization. This course may be helpful in understanding the components of a high-performing ML system that can be deployed and optimized in production environments.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of finance and economics to advise clients on investment opportunities. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks within organizations. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Product Manager
Product Manager
Product Managers are responsible for the development and introduction of new products, from initial concept all the way through to launch. This course may be useful in understanding the components of a high-performing ML system that will be deployed to production environments.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to solve business problems. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts apply advanced analytical methods to improve decision-making and problem-solving within organizations. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Statistician
Statistician
Statisticians apply their knowledge of statistical methods and techniques to collect, analyze, and interpret data. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Systems Analyst
Systems Analyst
Systems Analysts apply their knowledge of systems and procedures to improving how organizations harness technology and human resources. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty, particularly in the insurance and finance industries. This course may be useful in understanding the components of a high-performing ML system that can be deployed to production environments at scale.
For more career information including salaries, visit:
OpenCourser.com/course/u3thsq/production
Reading list
We haven't picked any books for this reading list yet.
This book, written by the Stanford University professor and former Chief Scientist at Baidu, provides a clear overview of machine learning with lots of diagrams and hands-on practice.
Provides a comprehensive and practical guide to deep learning, including hands-on exercises and real-world examples.
Classic text on machine learning and statistical pattern recognition, with a focus on Bayesian approaches. The author has won the prestigious Turing Award.
Provides a balanced treatment of both statistical and machine learning methods, making it accessible to a wide audience.
Practical guide to machine learning with Python, covering a wide range of topics from data preprocessing to model evaluation.
Gentle introduction to machine learning, suitable for those with no prior knowledge of the field, with a focus on understanding the concepts rather than the math.
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Provides a comprehensive treatment of machine learning from a probabilistic perspective, covering a wide range of topics from Bayesian inference to deep learning.
Practical guide to machine learning for programmers, with a focus on using Python to build and deploy machine learning models.
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Practical guide to machine learning for those with no prior experience, covering a wide range of topics from data preprocessing to model evaluation.
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Comprehensive and authoritative reference on deep learning, covering a wide range of topics from neural networks to reinforcement learning.
Practical guide to machine learning for those with no prior experience, covering a wide range of topics from data preprocessing to model evaluation. It great hands-on tutorial to pick up skills in machine learning.
While not focused specifically on Machine learning, this book covers a broad range of topics in Artificial Intelligence including machine learning, and good companion to delve deeper into the theoretical and technical aspects of the field.
Comprehensive overview of production and operations management, and it includes discussions on topics such as product design, process design, capacity planning, and inventory management. It would be a useful resource for anyone who wants to learn more about the field of production environments.
Discusses the latest trends in operations management, such as sustainability and supply chain management. It would be a valuable resource for anyone who wants to learn more about these topics and how they can be applied to production environments.
Provides a comprehensive overview of lean production, a manufacturing philosophy that focuses on waste reduction and efficiency. It would be a good choice for someone who wants to learn more about how to implement lean principles in a production environment.
Classic work on the Toyota Production System, a manufacturing philosophy that has been widely adopted by companies around the world. It would be a valuable resource for anyone who wants to learn more about the principles of lean production.
Provides a comprehensive overview of Six Sigma, a quality improvement methodology that has been used by companies around the world to improve their production processes. It would be a good choice for someone who wants to learn more about how to implement Six Sigma in a production environment.
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Novel that tells the story of a manufacturing plant that is struggling to meet its production goals. It provides a good overview of the principles of lean production and Six Sigma.
Provides a comprehensive overview of manufacturing planning and control, with a focus on supply chain management. It would be a good choice for someone who wants to learn more about how to manage production in a global supply chain.
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Provides a theoretical foundation for manufacturing management, with a focus on factory physics. It would be a good choice for someone who wants to learn more about the mathematical models that are used to analyze production environments.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/u3thsq/production
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Time
3 hours
Via
Pluralsight
Instructor
Authored by Google Cloud
This course belongs to a
collection
called
Advanced Machine Learning on Google Cloud. It's comprised of five courses:
Good to know
Taught by Google Cloud experts, recognized for their innovation in ML
Suitable for professionals wanting to build a high performing machine learning system for production
Delves into best practices for ML systems in production environments
Requires prior knowledge in ML and experience in production environments
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