Semantic Segmentation with Amazon Sagemaker
Prepare data for Sagemaker Semantic Segmentation.
Train a model using Sagemaker.
Deploy a trained model using Sagemaker.
Demuestra esta experiencia práctica en una entrevista
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 a Semantic Segmentation model using Amazon Sagemaker. Sagemaker provides a number of machine learning algorithms ready to be used for solving a number of tasks. We will use the semantic segmentation algorithm from Sagemaker to create, train and deploy a model that will be able to segment images of dogs and cats from the popular IIIT-Oxford Pets Dataset into 3 unique pixel values. That is, each pixel of an input image would be classified as either foreground (pet), background (not a pet), or unclassified (transition between foreground and background). Since this is a practical, project-based course, we will not dive in the theory behind deep learning based semantic segmentation, but will focus purely on training and deploying a model with Sagemaker. You will also need to have some experience with Amazon Web Services (AWS).
Python programming, conceptual understanding of deep learning, and previous experience with AWS is required.
Habilidades que desarrollarás
Aprende paso a paso
En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:
Introduction
Download the Data
Visualize the Data
Training Image
Preparing the Data
Uploading the Data to S3
Sagemaker Estimator
Hyperparameters
Data Channels
Model Training
Cómo funcionan los proyectos guiados
Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.
En un video de pantalla dividida, tu instructor te guía paso a paso
Reseñas
Principales reseñas sobre SEMANTIC SEGMENTATION WITH AMAZON SAGEMAKER
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Preguntas Frecuentes
Preguntas Frecuentes
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