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Amit Yadav

Please note: You will need an AWS account to complete this course. Your AWS account will be charged as per your usage. Please make sure that you are able to access Sagemaker within your AWS account. If your AWS account is new, you may need to ask AWS support for access to certain resources. You should be familiar with python programming, and AWS before starting this hands on project. We use a Sagemaker P type instance in this project, and if you don't have access to this instance type, please contact AWS support and request access.

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Please note: You will need an AWS account to complete this course. Your AWS account will be charged as per your usage. Please make sure that you are able to access Sagemaker within your AWS account. If your AWS account is new, you may need to ask AWS support for access to certain resources. You should be familiar with python programming, and AWS before starting this hands on project. We use a Sagemaker P type instance in this project, and if you don't have access to this instance type, please contact AWS support and request access.

In this 2-hour long project-based course, you will learn how to train and deploy an image classifier created and trained with the TensorFlow framework within the Amazon Sagemaker ecosystem. Sagemaker provides a number of machine learning algorithms ready to be used for solving a number of tasks. However, it is possible to use Sagemaker for custom training scripts as well. We will use TensorFlow and Sagemaker's TensorFlow Estimator to create, train and deploy a model that will be able to classify images of dogs and cats from the popular Oxford IIIT Pet Dataset.

Since this is a practical, project-based course, we will not dive in the theory behind deep learning based image classification, but will focus purely on training and deploying a model with Sagemaker and TensorFlow. You will also need to have some experience with Amazon Web Services (AWS).

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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What's inside

Syllabus

Using TensorFlow with Amazon Sagemaker
In this 2-hour long project-based course, you will learn how to train and deploy an image classifier created and trained with the TensorFlow framework within the Amazon Sagemaker ecosystem. Sagemaker provides a number of machine learning algorithms ready to be used for solving a number of tasks. However, it is possible to use Sagemaker for custom training scripts as well. We will use TensorFlow and Sagemaker's TensorFlow Estimator to create, train and deploy a model that will be able to classify images of dogs and cats from the popular Oxford IIIT Pet Dataset.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides hands-on training for building and deploying image classifiers with TensorFlow and Amazon SageMaker
Focuses on practical skills development through a project-based approach
Requires prior experience with Python programming and AWS
Uses Sagemaker P type instance, which may require additional access approval
Best suited for learners based in the North America region, with potential limitations for other regions

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Reviews summary

Helpful tensorflow on sagemaker course

Learners say this introductory course on TensorFlow with Amazon SageMaker is helpful, especially for those new to AWS SageMaker. While students describe the instructor as great, they also note that the course is short and assumes you will complete it in one session.
The instructor is great.
"The instructor is great, he tries his best to explain all steps."
This is an introductory course.
"This course will serve as a guide on how to use AWS SageMaker."
"Very useful and practical course covering the basics to train a Tensorflow model on Sagemaker."
Students describe the course as helpful.
"Very helpful."
"Very Interesting"
"Good tutorial for anyone new to AWS Sagemaker and wanting to learn how to deploy a basic TensorFlow model"
The course assumes you have some knowledge of AWS.
"You may also need general AWS knowledge."
The code is outdated.
"Code was a bit out dated."
The course is short.
"However, a short project is not enough to grasp all materials in AWS Sagemaker."
"The way the course is designed now it assumes that you work through it in one session."

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 Using TensorFlow with Amazon Sagemaker with these activities:
Review Book: Hands-On Machine Learning with TensorFlow
This book provides a comprehensive overview of TensorFlow and its applications in machine learning.
Show steps
  • Read the book and take notes on key concepts.
  • Try out the code examples provided in the book.
Join a TensorFlow community and help others
Engaging with the TensorFlow community can provide you with additional support and opportunities to share your knowledge.
Browse courses on TensorFlow
Show steps
  • Join a TensorFlow forum or discussion group.
  • Answer questions and provide assistance to others.
  • Contribute to open-source TensorFlow projects.
Review Python programming basics
Brushing up on Python programming fundamentals will provide you with a solid foundation for using TensorFlow and SageMaker.
Browse courses on Python Programming
Show steps
  • Review variables, data types, and operators.
  • Practice writing basic Python functions.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Review AWS basics
A basic understanding of AWS will help you navigate the SageMaker platform and its services.
Browse courses on AWS
Show steps
  • Review the AWS console and its features.
  • Practice creating and managing AWS resources.
Follow TensorFlow Tutorials on Image Classification
Following tutorials will help you learn the basics of TensorFlow and image classification.
Browse courses on TensorFlow
Show steps
  • Find online tutorials on TensorFlow image classification.
  • Follow the steps in the tutorials and try out the code examples.
Follow a TensorFlow tutorial on image classification
Working through a guided TensorFlow tutorial will provide you with hands-on experience in building and training image classification models.
Browse courses on TensorFlow
Show steps
  • Choose a suitable TensorFlow tutorial.
  • Follow the tutorial step-by-step.
  • Experiment with different parameters and architectures.
Join a Study Group on TensorFlow
Joining a study group will provide you with opportunities to discuss the course material and learn from others.
Browse courses on TensorFlow
Show steps
  • Find a study group or create your own.
  • Meet regularly with your group to discuss the course material.
  • Work together on assignments and projects.
Practice writing TensorFlow code for image classification
Regular practice in writing TensorFlow code will improve your proficiency and confidence in using the framework.
Browse courses on TensorFlow
Show steps
  • Create a new TensorFlow project.
  • Implement a basic image classification model.
  • Train and evaluate your model.
Mentor a Junior Student in TensorFlow
Mentoring others will help you reinforce your knowledge and develop your leadership skills.
Browse courses on TensorFlow
Show steps
  • Find a junior student who is interested in learning TensorFlow.
  • Meet with your mentee regularly to provide guidance and support.
Contribute to TensorFlow open-source projects
Contributing to open-source TensorFlow projects can enhance your understanding of the framework and its ecosystem.
Browse courses on TensorFlow
Show steps
  • Identify open-source TensorFlow projects that align with your interests.
  • Review the project's documentation and codebase.
  • Contribute bug fixes, feature enhancements, or documentation improvements.
Build a portfolio of image classification projects
Building a portfolio of image classification projects will showcase your skills and demonstrate your mastery of the concepts covered in this course.
Browse courses on TensorFlow
Show steps
  • Identify different image classification tasks.
  • Design and implement solutions using TensorFlow.
  • Document and present your projects.
Practice Solving Tensorflow Exercises
Solving Tensorflow exercises will help you solidify your understanding of the concepts taught in this course.
Browse courses on TensorFlow
Show steps
  • Find online resources or purchase books that provide TensorFlow exercises.
  • Set aside regular time each week to practice solving exercises.
  • Review your solutions and identify areas where you need improvement.
Create a Blog Post on TensorFlow Image Classification
Creating a blog post will help you organize your knowledge and share your understanding with others.
Browse courses on TensorFlow
Show steps
  • Choose a topic for your blog post.
  • Research the topic and gather information.
  • Write a draft of your blog post.
  • Edit and revise your blog post.
  • Publish your blog post.
Build an Image Classifier using TensorFlow
Building an image classifier will help you apply your knowledge and gain practical experience.
Browse courses on TensorFlow
Show steps
  • Gather a dataset of images.
  • Preprocess the images and prepare the data for training.
  • Build a TensorFlow model for image classification.
  • Train the model on the dataset.
  • Evaluate the performance of the model.
Participate in a TensorFlow Image Classification Competition
Participating in a competition will challenge you to apply your skills and push your limits.
Browse courses on TensorFlow
Show steps
  • Find a TensorFlow image classification competition.
  • Prepare your model and data for the competition.
  • Submit your model to the competition.
  • Monitor your results and make adjustments as needed.

Career center

Learners who complete Using TensorFlow with Amazon Sagemaker will develop knowledge and skills that may be useful to these careers:
Research Scientist
Research Scientists conduct research in the field of computer science. This course may be helpful in developing the skills you need to become a Research Scientist because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Research Scientists typically have a strong background in computer science and machine learning. This course may be especially helpful if you are interested in conducting research in the field of machine learning.
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. This course may be helpful in developing the skills you need to become a Machine Learning Engineer because it offers hands-on experience using TensorFlow and Amazon Sagemaker. Machine Learning Engineers typically have a strong background in computer science and machine learning.
AI Engineer
AI Engineers design, develop, and maintain AI systems. This course may be helpful in developing the skills you need to become an AI Engineer because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. AI Engineers typically have a strong background in computer science and artificial intelligence.
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course may be helpful in developing the skills you need to become a Data Engineer because it covers using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Data Engineers typically have a strong background in computer science and big data.
DevOps Engineer
DevOps Engineers build, deploy, and maintain software systems. This course may be helpful in developing the skills you need to become a DevOps Engineer because it provides experience in using TensorFlow and Amazon Sagemaker. DevOps Engineers typically have a strong background in computer science and software development. This course will help prepare you for a career as a DevOps Engineer by providing you with experience in using machine learning and cloud computing technologies.
Technical Architect
Technical Architects design and implement technical solutions for businesses. This course may be helpful in developing the skills you need to become a Technical Architect because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Technical Architects typically have a strong background in computer science and technology.
Cloud Architect
Cloud Architects design, build, and maintain cloud computing solutions. This course may be helpful in developing the skills you need to become a Cloud Architect because it provides experience in using TensorFlow and Amazon Sagemaker. Cloud Architects typically have a strong background in computer science and cloud computing. Pursuing this course may enhance your understanding of cloud architecture and how to implement machine learning solutions using cloud services.
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course may be helpful in developing the skills you need to become a Data Analyst because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Data Analysts typically have a strong background in mathematics, statistics, and computer science.
Software Developer
Software Developers design, develop, and maintain software applications. This course may be helpful in developing the skills you need to become a Software Developer because it provides experience in using TensorFlow and Amazon Sagemaker. Software Developers typically have a strong background in computer science and software development.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course may be helpful in developing the skills you need to become a Software Engineer because it provides experience in using TensorFlow and Amazon Sagemaker. Software Engineers typically have a strong background in computer science and software development. This course will help prepare you for a career as a software engineer by providing you with experience in using machine learning and cloud computing technologies.
Business Analyst
Business Analysts identify and solve business problems using data and technology. This course may be helpful in developing the skills you need to become a Business Analyst because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Business Analysts typically have a strong background in business and technology.
Solutions Architect
In this increasingly digital world, Solutions Architects are in high demand. This course may be helpful in developing the skills you need to become a Solutions Architect because it covers using TensorFlow with Amazon Sagemaker. Solutions Architects help clients understand and implement technological solutions to their business problems. They typically have a deep understanding of cloud computing and software development. Pursuing this course would provide you with a foundational understanding of how to apply TensorFlow in deploying image classification models using Amazon Sagemaker.
Product Manager
Product Managers define and manage the development of products. This course may be helpful in developing the skills you need to become a Product Manager because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Product Managers typically have a strong background in business, technology, and product management.
Data Scientist
Data Scientists are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course may be helpful in developing the skills you need to become a Data Scientist because it will enable you to use TensorFlow with Amazon Sagemaker to build and deploy predictive models. Data Scientists typically have a strong background in mathematics, statistics, and computer science.
Project Manager
Project Managers plan, execute, and close projects. This course may be helpful in developing the skills you need to become a Project Manager because it provides experience in using TensorFlow and Amazon Sagemaker to build and deploy machine learning models. Project Managers typically have a strong background in project management and technology.

Reading list

We've selected six 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 Using TensorFlow with Amazon Sagemaker.
Provides an introduction to deep learning using R, offering an alternative perspective to the course's focus on Python.

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