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David Tucker
This course will cover the launching and configuration of EC2 instances using the Deep Learning AMIs provided by AWS as well as leveraging the included deep learning frameworks.
Read more
This course will cover the launching and configuration of EC2 instances using the Deep Learning AMIs provided by AWS as well as leveraging the included deep learning frameworks.
Read more
This course will cover the launching and configuration of EC2 instances using the Deep Learning AMIs provided by AWS as well as leveraging the included deep learning frameworks.
Deep learning enables a new level of data analysis, but configuring custom compute resources to gain these insights can be extremely difficult. In this course, Deep Learning Instances and Frameworks on AWS, you will gain the ability to launch deep learning instances on EC2 and ECS. First, you will learn the types of Deep Learning AMIs provided by AWS. Next, you will analyze how to leverage popular deep learning frameworks on these instances. Finally, you will review how to manage and scale your deep learning activities on these instances. When you are finished with this course, you will be able to launch and utilize custom deep learning instances and leverage popular deep learning frameworks.
Register for this course and see more details by visiting:
OpenCourser.com/course/putvaj/deep
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What's inside
Syllabus
Course Overview
Introduction to Deep Learning AMIs
Leveraging Deep Learning AMIs
Managing Deep Learning Instances
Read more
Syllabus
Course Overview
Introduction to Deep Learning AMIs
Leveraging Deep Learning AMIs
Managing Deep Learning Instances
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops deep learning skills, which are valuable in many industries
Taught by David Tucker, who are recognized for their expertise in building deep learning systems
Multi-modal course includes videos, readings, and hands-on labs to enhance learning
Requires learners to have some background knowledge in deep learning
Course content may not be up-to-date with the latest advancements in deep learning
Assumes learners have access to specialized hardware for deep learning tasks
Save this course
Save Deep Learning Instances and Frameworks on AWS to your list so you can find it easily later:
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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 Deep Learning Instances and Frameworks on AWS with these
activities:
Review Amazon Web Services Concepts
Show steps
Review basic AWS concepts to ensure a solid foundation for the course.
Browse courses on
AWS
Show steps
-
Read AWS documentation on EC2 instances.
-
Practice launching and configuring EC2 instances in a sandbox environment.
Review fundamentals of machine learning
Show steps
Help learners with prerequisite skills and knowledge needed to understand the course content.
Browse courses on
Machine Learning
Show steps
-
Revise basic concepts of machine learning such as supervised and unsupervised learning.
-
Refresh your understanding of machine learning algorithms such as linear regression and decision trees.
Review deep learning concepts
Show steps
Ensure learners have a strong foundation in deep learning before starting the course.
Browse courses on
Deep Learning
Show steps
-
Review deep learning concepts such as neural networks, convolutional neural networks, and recurrent neural networks.
-
Refresh your understanding of deep learning frameworks such as TensorFlow or PyTorch.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete AWS Deep Learning Workshops
Show steps
Follow official AWS workshops to gain practical experience in setting up and using deep learning environments.
Show steps
-
Sign up for AWS Deep Learning workshops.
-
Follow the workshop exercises on setting up and configuring deep learning instances.
-
Complete the exercises and explore the provided code examples.
Join a Study Group for AWS Deep Learning
Show steps
Collaborate with peers to enhance understanding and tackle challenges together.
Browse courses on
Collaboration
Show steps
-
Find or start a study group focused on AWS Deep Learning.
-
Meet regularly to discuss course materials, share knowledge, and work through problems.
Create a Deep Learning Project on AWS
Show steps
Apply your knowledge by building a small deep learning project using AWS services.
Browse courses on
AWS EC2
Show steps
-
Choose a deep learning task and gather the necessary data.
-
Launch a suitable EC2 instance and install the required deep learning libraries.
-
Develop and train a deep learning model.
-
Evaluate and deploy your model.
Start a long-term deep learning project
Show steps
Encourage learners to engage in long-term projects to deepen their understanding and develop practical skills.
Show steps
-
Start a long-term deep learning project that involves collecting, cleaning, and analyzing a dataset.
-
The project can be related to any domain of interest, such as healthcare, finance, or natural language processing.
Participate in AWS Deep Learning Challenges
Show steps
Test your skills and gain practical experience by participating in AWS Deep Learning challenges.
Browse courses on
Challenges
Show steps
-
Find and register for relevant AWS Deep Learning challenges.
-
Develop and submit your solutions to the challenges.
-
Review feedback and learn from your participation.
Review Amazon Web Services Concepts
Show steps
Review basic AWS concepts to ensure a solid foundation for the course.
Browse courses on
AWS
Show steps
Show steps
Show steps
- Read AWS documentation on EC2 instances.
- Practice launching and configuring EC2 instances in a sandbox environment.
Review fundamentals of machine learning
Show steps
Help learners with prerequisite skills and knowledge needed to understand the course content.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Revise basic concepts of machine learning such as supervised and unsupervised learning.
- Refresh your understanding of machine learning algorithms such as linear regression and decision trees.
Review deep learning concepts
Show steps
Ensure learners have a strong foundation in deep learning before starting the course.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Review deep learning concepts such as neural networks, convolutional neural networks, and recurrent neural networks.
- Refresh your understanding of deep learning frameworks such as TensorFlow or PyTorch.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete AWS Deep Learning Workshops
Show steps
Follow official AWS workshops to gain practical experience in setting up and using deep learning environments.
Show steps
Show steps
Show steps
- Sign up for AWS Deep Learning workshops.
- Follow the workshop exercises on setting up and configuring deep learning instances.
- Complete the exercises and explore the provided code examples.
Join a Study Group for AWS Deep Learning
Show steps
Collaborate with peers to enhance understanding and tackle challenges together.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find or start a study group focused on AWS Deep Learning.
- Meet regularly to discuss course materials, share knowledge, and work through problems.
Create a Deep Learning Project on AWS
Show steps
Apply your knowledge by building a small deep learning project using AWS services.
Browse courses on
AWS EC2
Show steps
Show steps
Show steps
- Choose a deep learning task and gather the necessary data.
- Launch a suitable EC2 instance and install the required deep learning libraries.
- Develop and train a deep learning model.
- Evaluate and deploy your model.
Start a long-term deep learning project
Show steps
Encourage learners to engage in long-term projects to deepen their understanding and develop practical skills.
Show steps
Show steps
Show steps
- Start a long-term deep learning project that involves collecting, cleaning, and analyzing a dataset.
- The project can be related to any domain of interest, such as healthcare, finance, or natural language processing.
Participate in AWS Deep Learning Challenges
Show steps
Test your skills and gain practical experience by participating in AWS Deep Learning challenges.
Browse courses on
Challenges
Show steps
Show steps
Show steps
- Find and register for relevant AWS Deep Learning challenges.
- Develop and submit your solutions to the challenges.
- Review feedback and learn from your participation.
Career center
Learners who complete Deep Learning Instances and Frameworks on AWS will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist can use their knowledge of deep learning frameworks to extract meaningful insights from big data. This course helps build a foundation in deep learning instances and frameworks on AWS. This foundation can be used to develop new models and improve existing ones.
Deep Learning Researcher
Deep Learning Researcher
Deep Learning Researchers may use deep learning instances and frameworks to conduct research in the field of deep learning. This course helps build a foundation in deep learning instances and frameworks on AWS, which can be used to develop new deep learning algorithms and models.
Data Analyst
Data Analyst
Data Analysts may use deep learning instances and frameworks to analyze big data. This course can help Data Analysts build a foundation in deep learning instances and frameworks on AWS, which can be used to develop new data analysis tools and techniques.
Data Science Manager
Data Science Manager
Data Science Managers may lead teams of data scientists who use deep learning instances and frameworks. This course can help Data Science Managers build a foundation in deep learning instances and frameworks on AWS, which can be used to make informed decisions about the use of these technologies.
Cloud Solutions Architect
Cloud Solutions Architect
Cloud Solutions Architects may design and implement cloud-based solutions for clients. This course can help Cloud Solutions Architects build a foundation in deep learning instances and frameworks on AWS, which can be used to develop and implement deep learning solutions in the cloud.
DevOps Engineer
DevOps Engineer
DevOps Engineers may work with teams to deploy and manage deep learning solutions. This course can help DevOps Engineers build a foundation in deep learning instances and frameworks on AWS, which can be used to develop and implement automated deployment and management processes.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts may use deep learning instances and frameworks to analyze big data. This course can help Business Intelligence Analysts build a foundation in deep learning instances and frameworks on AWS, which can be used to develop new business intelligence tools and techniques.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers may use deep learning instances and frameworks to develop AI solutions. This course may be particularly useful to those interested in learning about deep learning AMIs and how to use them to train and evaluate AI models.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts may use deep learning instances and frameworks to analyze financial data. This course can help Quantitative Analysts build a foundation in deep learning instances and frameworks on AWS, which can be used to develop new financial analysis tools and techniques.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers may leverage deep learning instances and frameworks to create and deploy machine learning models. This course may be particularly useful to those interested in learning about deep learning AMIs and how to use them to train and evaluate models.
IT Consultant
IT Consultant
IT Consultants may work with clients to implement deep learning solutions. This course can help IT Consultants build a foundation in deep learning instances and frameworks on AWS, which can be used to provide informed advice to clients about the use of these technologies.
Product Manager
Product Manager
Product Managers may work with engineers to develop deep learning products and services. This course can help Product Managers build a foundation in deep learning instances and frameworks on AWS, which can be used to make informed decisions about the development and deployment of these products and services.
Software Engineer
Software Engineer
Software Engineers may use deep learning instances and frameworks to develop deep learning applications. This course may be particularly useful to those interested in learning about deep learning AMIs and how to use them to train and deploy deep learning models.
Cloud Architect
Cloud Architect
Cloud Architects help organizations design and implement cloud-based solutions. This course may be useful to Cloud Architects who want to learn more about deep learning instances and frameworks on AWS. This knowledge can be used to develop and deploy deep learning solutions in the cloud.
Technical Writer
Technical Writer
Technical Writers who specialize in deep learning may use deep learning instances and frameworks to develop documentation. This course can help Technical Writers build a foundation in deep learning instances and frameworks on AWS, which can be used to create accurate and informative documentation.
For more career information including salaries, visit:
OpenCourser.com/course/putvaj/deep
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
Deep Learning Instances and Frameworks on AWS.
Provides a comprehensive overview of deep learning techniques for computer vision tasks, covering topics such as image classification, object detection, and semantic segmentation. It valuable resource for those looking to gain a deeper understanding of the field and its applications.
Provides a comprehensive overview of deep learning, covering the latest techniques and models. It valuable resource for anyone who wants to learn more about deep learning, from beginners to experienced practitioners.
Save
Comprehensive reference on deep learning. It covers a wide range of topics, from the basics of neural networks to advanced topics such as generative adversarial networks and reinforcement learning. It valuable resource for both researchers and practitioners.
Provides a comprehensive overview of deep learning for natural language processing, covering the latest techniques and models. It valuable resource for anyone who wants to learn more about deep learning for NLP, from beginners to experienced practitioners.
Provides a comprehensive overview of deep learning with Ruby, covering the latest techniques and models. It valuable resource for anyone who wants to learn more about deep learning with Ruby, from beginners to experienced practitioners.
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, from statistical foundations to advanced algorithms. It valuable resource for both researchers and practitioners.
Provides a practical guide to machine learning, covering the essential concepts and techniques. It good choice for beginners who want to learn how to apply machine learning to real-world problems.
Provides a practical introduction to machine learning using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including data preprocessing, model selection, and evaluation, making it a valuable resource for both beginners and experienced practitioners.
Provides a comprehensive overview of deep learning with R, covering the latest techniques and models. It valuable resource for anyone who wants to learn more about deep learning with R, from beginners to experienced practitioners.
Save
Provides a comprehensive overview of machine learning. It covers a wide range of topics, from the basics of supervised and unsupervised learning to advanced topics such as reinforcement learning and Bayesian methods. It valuable resource for both researchers and practitioners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/putvaj/deep
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Time
83 hours
Level
Intermediate
Via
Pluralsight
Instructor
David Tucker
Language
English
This course belongs to a
collection
called
AWS Machine Learning / AI. It's comprised of nine courses:
- Getting Started with Amazon Lex
- Building a Voice-enabled Serverless Website with AWS Polly
- Translating Languages on AWS with Amazon Translate
- Developing Applications with AWS Rekognition
- Analyzing Text on AWS with Amazon Comprehend
- Turning Speech into Text on AWS with Amazon Transcribe
- Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1
- Deep Learning Instances and Frameworks on AWS (viewing)
- Extracting Text and Data with Amazon Textract
Good to know
Develops deep learning skills, which are valuable in many industries
Taught by David Tucker, who are recognized for their expertise in building deep learning systems
Multi-modal course includes videos, readings, and hands-on labs to enhance learning
Requires learners to have some background knowledge in deep learning
Course content may not be up-to-date with the latest advancements in deep learning
Assumes learners have access to specialized hardware for deep learning tasks
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