Deep Learning on AWS
Deploy cloud-based deep learning models using AWS services.
Deep Learning on AWS is a one-day course that introduces you to cloud-based Deep Learning (DL) solutions on Amazon Web Services (AWS). The training will detail how deep learning is useful and explain its different concepts. This course also teaches you how to run your models on the cloud using Amazon SageMaker, Amazon Elastic Compute Cloud (Amazon EC2)-based Deep Learning Amazon Machine Image (AMI) and MXNet framework. In addition, you will gain a better understanding of deploying your deep learning models using AWS services like AWS Lambda and Amazon EC2 Container Service (Amazon ECS) while designing intelligent systems on AWS, based on Deep Learning
Available formats for this course
Duration1 day/8 hours of instruction
Public Classroom Pricing
Group Rate: $675
Get the full details on this course. Download the .PDF Brochure below:
Part 1: Introduction to Machine Learning
Part 2: Introduction to Deep Learning
Part 3: Setting up a Deep Learning AMI instance and running a multilayer perceptron model
Part 4: Introduction to MXNet on AWS
Part 5: Running a convolutional neural network model and predicting images on CIFAR-10 dataset
Part 6: Deploying Deep Learning Workloads on AWS
Part 7: Deploying a Deep Learning model for predicting images using AWS Lambda
- Define machine learning and deep learning
- Identify the concepts in a deep learning ecosystem
- Leverage Amazon SageMaker and MXNet programming framework for deep learning workloads
- Fit AWS solutions for deep learning deployments
A full refund will be issued for class cancellations made at least 10 business days before the course begins. Payment is non‑refundable for cancellations or reschedules made within 10 business days from the course start date and for No‑Shows (students who do not attend class).
For reschedules made within 10 business days from the course start date, students must reschedule immediately for a current, published course, up to a maximum of six months from the original date.
A student may reschedule a class or exam up to 2 times. Any additional reschedules will not be allowed.