Deep Learning on AWS.
This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises. This course will be delivered through a mix of instructor-led training (ILT) and hands-on labs
About the course
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 and MXNet framework. In addition, you will gain a better understanding 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.
This course is intended for
- Developers who are responsible for developing deep learning applications
- Developers who want to understand concepts behind deep learning and how to implement a deep learning solution on AWS
Prerequisites
- Basic understanding of machine learning processes
- Basic understanding of AWS core services like Amazon EC2 and knowledge of AWS SDK
- Basic knowledge of a scripting language e.g. Python
This course is designed to teach you how to:
- Define machine learning and deep learning
- Identify the concepts in a deep learning ecosystem
- Leverage Amazon SageMaker and MXNet programming frameworks for deep learning workloads
- Fit AWS solutions for deep learning deployments
Agenda
Day One
- Module 1: A Machine Learning Overview
- Module 2: Introduction to Deep Learning
- Lab 1: Spinning up an Amazon SageMaker instance and running a multi-layer perceptron neural network model
- Module 3: Introduction to Apache MXNet
- Lab 2: Running a Convolutional Neural Network (CNN) model to predicting images using CIFAR 10 dataset
- Module 4: ML and DL Architectures on AWS
- Lab 3: Deploying a deep learning model for predicting images using AWS Lambda
Schedule & Locations
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