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Deep Learning on AWS (AWSDL)

 

Course Content

  • Introduction to Machine Learning
  • Introduction to Deep Learning
  • Lab 1: Spinning up Amazon Deep Learning AMI based on EC2 and preprocessing data
  • Introduction to MXNet on AWS
  • Lab 2: Running a Convolutional Neural Network model and predicting images
  • Deploying Deep Learning Workloads on AWS
  • Lab 3: Deploying Deep Learning model for predicting images using AWS Lambda

Who should attend

This course is intended for:

  • Developers responsible for developing DL applications
  • Developers who want to understand concepts behind deep learning and how to implement a DL solution on AWS

Prerequisites

We recommend that attendees of this course have the following prerequisites:

  • Basic understanding of ML processes
  • Basic understanding of AWS core services like EC2 and knowledge of AWS SDK
  • Basic knowledge of a scripting language e.g. Python

Course Objectives

Deep Learning ILT introduces you to cloud based deep learning solutions on AWS. In this course, we will detail how deep learning is useful and explain the different concepts in deep learning. This course also teaches you how to run your models on the cloud using Amazon EC2 based Deep Learning AMI and MXNet framework. This course will help you gain a better understanding of deploying your deep learning models using AWS services like AWS Lambda, Amazon EC2 Container Service (ECS) while designing intelligent systems on AWS based on deep learning.

Classroom Training

Duration 1 day

Price
  • United States: US$ 675
Online Training

Duration 1 day

Price
  • United States: US$ 675
 
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This is an Instructor-Led Classroom course
This is a FLEX course, which is delivered simultaneously in two modalities. Choose to attend the Instructor-Led Online (ILO) virtual session or Instructor-Led Classroom (ILT) session.
United States

Currently there are no training dates scheduled for this course.  You can schedule a private, onsite training session or request a public date by emailing info@fastlaneus.com.

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