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In this video, you will learn about machine learning inference processing challenges and use cases, and get an understanding of the AWS solution to help solve the challenges using Amazon EC2 Inf1 instances powered by AWS Inferentia.
Read more
In this video, you will learn about machine learning inference processing challenges and use cases, and get an understanding of the AWS solution to help solve the challenges using Amazon EC2 Inf1 instances powered by AWS Inferentia.
Read more
In this video, you will learn about machine learning inference processing challenges and use cases, and get an understanding of the AWS solution to help solve the challenges using Amazon EC2 Inf1 instances powered by AWS Inferentia.
In this video, you will learn about machine learning inference processing challenges and use cases, and get an understanding of the AWS solution to help solve the challenges using Amazon EC2 Inf1 instances powered by AWS Inferentia. You’ll get an understanding of AWS Inferentia custom chips designed for machine learning inference processing, and AWS Neuron SDK enabling high-performance deep learning inference using AWS Inferentia.
Register for this course and see more details by visiting:
OpenCourser.com/course/rtm1ck/introduction
What's inside
Syllabus
Introduction to AWS Inferentia and Amazon EC2 Inf1 Instances
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills relevant to using AWS cloud computing services, which is an industry standard toolset
Taught by experts from AWS, recognized for their work in machine learning and cloud computing
Teaches methods for optimizing machine learning inference processing, which is a key component of machine learning systems
Covers key concepts of machine learning inference processing, such as deployment and optimization
Introduces students to AWS Neuron SDK, a framework for developing high-performance deep learning inference using AWS Inferentia
Requires students have prior knowledge of machine learning and cloud computing
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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 Introduction to AWS Inferentia and Amazon EC2 Inf1 Instances with these
activities:
Join a study group to discuss AWS Inferentia and machine learning inference
Show steps
Enhance your understanding through collaboration and peer support by joining a study group where you can discuss AWS Inferentia, machine learning inference, and related concepts with fellow learners.
Show steps
-
Find or create a study group
-
Set regular meeting times
-
Discuss course materials and share insights
Attend an online workshop on AWS Inferentia and its applications
Show steps
Enhance your knowledge and skills by attending an online workshop dedicated to AWS Inferentia and its applications, providing you with interactive learning and networking opportunities.
Show steps
-
Find and register for a relevant workshop
-
Attend the workshop and participate actively
-
Follow up on any resources or connections made
Follow tutorials on implementing AWS Inferentia for ML inference
Show steps
Supplement your understanding of AWS Inferentia by following guided tutorials, providing hands-on experience in implementing and utilizing this technology for machine learning inference tasks.
Show steps
-
Find relevant tutorials on AWS Inferentia
-
Follow the tutorials step-by-step
-
Test the implementation
Four other activities
Expand to see all activities and additional details
Show all seven activities
Become a mentor for fellow learners exploring AWS Inferentia
Show steps
Reinforce your learning by sharing your knowledge and providing guidance to fellow learners who are interested in exploring AWS Inferentia, fostering a collaborative learning environment.
Show steps
-
Identify opportunities to mentor others
-
Provide support and guidance on AWS Inferentia concepts
-
Share your experiences and best practices
Practice deploying and monitoring AWS EC2 Inf1 instances
Show steps
Reinforce your understanding of the practical aspects of deploying and monitoring AWS EC2 Inf1 instances, enhancing your ability to apply these skills in real-world scenarios.
Browse courses on
AWS Cloud Services
Show steps
-
Set up an AWS account and EC2 instance
-
Deploy a sample application
-
Monitor the instance's performance
Develop a proof-of-concept solution using AWS Inferentia and EC2 Inf1 instances
Show steps
Solidify your learning by applying your knowledge to a practical project where you develop and implement a proof-of-concept solution using AWS Inferentia and EC2 Inf1 instances, gaining valuable hands-on experience.
Show steps
-
Define a use case and problem statement
-
Design and implement the solution
-
Test and evaluate the solution
Write a blog post or article on a specific aspect of AWS Inferentia
Show steps
Deepen your understanding by creating a piece of written content that explores a specific aspect of AWS Inferentia, allowing you to synthesize your knowledge and share it with others.
Show steps
-
Choose a topic and research the subject
-
Develop an outline and write the content
-
Edit and refine your writing
Join a study group to discuss AWS Inferentia and machine learning inference
Show steps
Enhance your understanding through collaboration and peer support by joining a study group where you can discuss AWS Inferentia, machine learning inference, and related concepts with fellow learners.
Show steps
Show steps
Show steps
- Find or create a study group
- Set regular meeting times
- Discuss course materials and share insights
Attend an online workshop on AWS Inferentia and its applications
Show steps
Enhance your knowledge and skills by attending an online workshop dedicated to AWS Inferentia and its applications, providing you with interactive learning and networking opportunities.
Show steps
Show steps
Show steps
- Find and register for a relevant workshop
- Attend the workshop and participate actively
- Follow up on any resources or connections made
Follow tutorials on implementing AWS Inferentia for ML inference
Show steps
Supplement your understanding of AWS Inferentia by following guided tutorials, providing hands-on experience in implementing and utilizing this technology for machine learning inference tasks.
Show steps
Show steps
Show steps
- Find relevant tutorials on AWS Inferentia
- Follow the tutorials step-by-step
- Test the implementation
Four other activities
Expand to see all activities and additional details
Show all seven activities
Become a mentor for fellow learners exploring AWS Inferentia
Show steps
Reinforce your learning by sharing your knowledge and providing guidance to fellow learners who are interested in exploring AWS Inferentia, fostering a collaborative learning environment.
Show steps
Show steps
Show steps
- Identify opportunities to mentor others
- Provide support and guidance on AWS Inferentia concepts
- Share your experiences and best practices
Practice deploying and monitoring AWS EC2 Inf1 instances
Show steps
Reinforce your understanding of the practical aspects of deploying and monitoring AWS EC2 Inf1 instances, enhancing your ability to apply these skills in real-world scenarios.
Browse courses on
AWS Cloud Services
Show steps
Show steps
Show steps
- Set up an AWS account and EC2 instance
- Deploy a sample application
- Monitor the instance's performance
Develop a proof-of-concept solution using AWS Inferentia and EC2 Inf1 instances
Show steps
Solidify your learning by applying your knowledge to a practical project where you develop and implement a proof-of-concept solution using AWS Inferentia and EC2 Inf1 instances, gaining valuable hands-on experience.
Show steps
Show steps
Show steps
- Define a use case and problem statement
- Design and implement the solution
- Test and evaluate the solution
Write a blog post or article on a specific aspect of AWS Inferentia
Show steps
Deepen your understanding by creating a piece of written content that explores a specific aspect of AWS Inferentia, allowing you to synthesize your knowledge and share it with others.
Show steps
Show steps
Show steps
- Choose a topic and research the subject
- Develop an outline and write the content
- Edit and refine your writing
Career center
Learners who complete Introduction to AWS Inferentia and Amazon EC2 Inf1 Instances will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers research, develop, and deploy machine learning models. They are responsible for ensuring that these models are accurate, efficient, and scalable. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for developing and deploying machine learning models. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Machine Learning Engineers to develop and deploy more efficient and scalable models.
Cloud Architect
Cloud Architect
Cloud Architects design, build, and maintain cloud computing systems. They are responsible for ensuring that these systems are scalable, secure, and reliable. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for designing and building cloud computing systems that can support machine learning applications. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Cloud Architects to design and build more efficient and scalable systems.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They are responsible for collecting, cleaning, and analyzing data to identify trends and insights. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for developing and deploying machine learning models that can be used to solve business problems. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Data Scientists to develop and deploy more efficient and scalable models.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They are responsible for ensuring that these applications are efficient, reliable, and secure. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for developing and deploying software applications that can support machine learning. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Software Engineers to develop and deploy more efficient and scalable applications.
DevOps Engineer
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations teams. They are responsible for ensuring that software applications are deployed and maintained efficiently and reliably. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for understanding the challenges and opportunities of deploying machine learning models. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help DevOps Engineers to deploy and maintain machine learning models more efficiently and reliably.
Data Analyst
Data Analyst
Data Analysts use data to identify trends and insights. They are responsible for collecting, cleaning, and analyzing data to help businesses make better decisions. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for understanding the challenges and opportunities of using machine learning to analyze data. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Data Analysts to use machine learning more efficiently and effectively.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. They are responsible for pushing the boundaries of machine learning and developing new ways to solve problems. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for understanding the challenges and opportunities of developing new machine learning algorithms. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Machine Learning Researchers to develop and deploy new algorithms more efficiently and effectively.
Business Analyst
Business Analyst
Business Analysts work with businesses to identify and solve problems. They are responsible for understanding the business needs and developing solutions that meet those needs. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for understanding the challenges and opportunities of using machine learning to solve business problems. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Business Analysts to develop and implement machine learning solutions more efficiently and effectively.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They are responsible for understanding the customer needs and developing products that meet those needs. This course provides a foundation in the fundamentals of machine learning inference processing, which is essential for understanding the challenges and opportunities of using machine learning to develop new products. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Product Managers to develop and launch new products more efficiently and effectively.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. They are responsible for understanding the target audience and developing campaigns that reach and engage that audience. This course may provide a foundation in the fundamentals of machine learning inference processing, which can be useful for understanding the challenges and opportunities of using machine learning to develop and execute marketing campaigns. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Marketing Managers to develop and execute more efficient and effective campaigns.
Sales Manager
Sales Manager
Sales Managers are responsible for leading and managing sales teams. They are responsible for developing and executing sales strategies and achieving sales targets. This course may provide a foundation in the fundamentals of machine learning inference processing, which can be useful for understanding the challenges and opportunities of using machine learning to develop and execute sales strategies. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Sales Managers to develop and execute more efficient and effective strategies.
Operations Manager
Operations Manager
Operations Managers are responsible for the day-to-day operations of a business. They are responsible for ensuring that the business runs smoothly and efficiently. This course may provide a foundation in the fundamentals of machine learning inference processing, which can be useful for understanding the challenges and opportunities of using machine learning to improve operations. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Operations Managers to develop and implement more efficient and effective operations.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data to make investment recommendations. They are responsible for understanding the financial markets and making recommendations that meet the investment objectives of their clients. This course may provide a foundation in the fundamentals of machine learning inference processing, which can be useful for understanding the challenges and opportunities of using machine learning to analyze financial data. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Financial Analysts to develop and implement more efficient and effective analysis.
Human Resources Manager
Human Resources Manager
Human Resources Managers are responsible for managing the human resources of a business. They are responsible for recruiting, hiring, and developing employees. This course may provide a foundation in the fundamentals of machine learning inference processing, which can be useful for understanding the challenges and opportunities of using machine learning to improve human resources processes. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Human Resources Managers to develop and implement more efficient and effective processes.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with a company's products or services. They are responsible for building relationships with customers and resolving any issues that they may have. This course may provide a foundation in the fundamentals of machine learning inference processing, which can be useful for understanding the challenges and opportunities of using machine learning to improve customer service. The course also covers the AWS solution for solving challenges in machine learning inference processing, which can help Customer Success Managers to develop and implement more efficient and effective customer service processes.
For more career information including salaries, visit:
OpenCourser.com/course/rtm1ck/introduction
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
Introduction to AWS Inferentia and Amazon EC2 Inf1 Instances.
A comprehensive textbook that introduces machine learning from a probabilistic perspective, providing a strong theoretical foundation.
A widely used textbook covering statistical learning methods and their applications in machine learning.
A comprehensive and practical guide to deep learning using Python and Keras, written by the creator of Keras.
A practical guide to applied machine learning, covering real-world scenarios and case studies.
A practical guide to building and deploying machine learning models using popular libraries like Scikit-Learn, Keras, and TensorFlow.
A practical guide to deep reinforcement learning, providing hands-on experience with designing and training deep reinforcement learning models.
Covers essential deep learning concepts, model training, and optimization techniques using PyTorch, providing a practical understanding of deep learning implementation.
Provides a gentle introduction to machine learning using Python, suitable for beginners with no prior knowledge.
A conceptual and intuitive guide to deep learning, suitable for readers with little to no background in the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rtm1ck/introduction
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Time
13 hours
Level
Introductory
Via
Pluralsight
Instructor
AWS
Language
English
Good to know
Develops skills relevant to using AWS cloud computing services, which is an industry standard toolset
Taught by experts from AWS, recognized for their work in machine learning and cloud computing
Teaches methods for optimizing machine learning inference processing, which is a key component of machine learning systems
Covers key concepts of machine learning inference processing, such as deployment and optimization
Introduces students to AWS Neuron SDK, a framework for developing high-performance deep learning inference using AWS Inferentia
Requires students have prior knowledge of machine learning and cloud computing
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