Deep Learning Inference with Azure ML Studio

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Neste projeto guiado, você irá:

Train and evaluate a multiclass neural network on Azure ML Studio to recognize handwritten digits

Create and deploy a predictive web service

Build a Python web app to query the Azure web service API for deep learning inference

Clock1.5 hours
BeginnerBásico
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

In this project-based course, you will use the Multiclass Neural Network module in Azure Machine Learning Studio to train a neural network to recognize handwritten digits. Microsoft Azure Machine Learning Studio is a drag-and-drop tool you can use to rapidly build and deploy machine learning models on Azure. The data used in this course is the popular MNIST data set consisting of 70,000 grayscale images of hand-written digits. You are going to deploy the trained neural network model as an Azure Web service. Azure Web Services provide an interface between an application and a Machine Learning Studio workflow scoring model. You will write a Python application to use the Batch Execution Service and predict the class labels of handwritten digits. This is the third course in this series on building machine learning applications using Azure Machine Learning Studio. I highly encourage you to take the first course before proceeding. It has instructions on how to set up your Azure ML account with $200 worth of free credit to get started with running your experiments! This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - 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.

Habilidades que você desenvolverá

azure-machine-learningdata-scienceartificial-intelligencemachine-learningdeep-learning

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  1. Introduction and Overview

  2. Data Preparation

  3. Train and Evaluate Multiclass Neural Network

  4. Create and Deploy Predictive Web Service

  5. Inference Using the Web Service API

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

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