Predictive Modelling with Azure Machine Learning Studio

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在此指导项目中,您将:

Build a predictive model using Azure ML Studio

Demonstrate a working knowledge of setting up experiments on Azure ML Studio

Operationalise machine learning workflows with Azure's drag-and-drop modules

Clock2 hours
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this project, we will use Azure Machine Learning Studio to build a predictive model without writing a single line of code! Specifically, we will predict flight delays using weather data provided by the US Bureau of Transportation Statistics and the National Oceanic and Atmospheric Association (NOAA). You will be provided with instructions on how to set up your Azure Machine Learning 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: - 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.

您要培养的技能

  • Data Science
  • Artificial Intelligence (AI)
  • Machine Learning
  • Data Analysis
  • Microsoft Azure

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Introduction and Setup Instructions

  2. Importing the Data Sets

  3. Scrubbing Missing Values

  4. Eliminating Target Leaks

  5. Conversion to Categorical Features

  6. Preparing Features to be Joined with Weather Data

  7. Preprocessing the Weather Dataset

  8. Joining Both Datasets

  9. Training and Evaluating the Model

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

授课教师

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