Build Random Forests in R with Azure ML Studio

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Coursera Project Network
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在此指導項目中,您將:

Train and evaluate a regression model on Azure ML Studio

Perform feature Engineering and data pre-processing using custom R scripts

Write custom machine learning models in R

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this project-based course you will learn to perform feature engineering and create custom R models on Azure ML Studio, all without writing a single line of code! You will build a Random Forests model in Azure ML Studio using the R programming language. The data to be used in this course is the Bike Sharing Dataset. The dataset contains the hourly and daily count of rental bikes between years 2011 and 2012 in Capital bikeshare system with the corresponding weather and seasonal information. Using the information from the dataset, you can build a model to predict the number of bikes rented during certain weather conditions. You will leverage the Execute R Script and Create R Model modules to run R scripts from the Azure ML Studio experiment perform feature engineering. This is the fourth 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.

您要培養的技能

Data Scienceazure-machine-learningArtificial Intelligence (AI)Machine LearningRandom Forest

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction and Overview

  2. Feature Engineering and Preprocessing

  3. Removing Outliers

  4. Model Building and Training

  5. Scoring and Evaluating the Models

  6. Model Evaluation

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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