Overview This guide takes you through the steps to create an environment for performing the data science experiments described in this repository. To prepare the lab environment, you must perform the following tasks: 1. Create an Azure ML account 2. Download and extract the lab files
What You’ll Need To perform the setup tasks, you will need the following:
A Windows, Linux, or Mac OSX computer.
A web browser and Internet connection.
Create an Azure ML Account Azure ML offers a free-tier account, which you can use to complete the labs in this repository. Note: A free Azure ML workspace is not the same as a Microsoft Azure trial subscription!
Sign Up for a Microsoft Account and a Free Azure ML Workspace 1. 2.
If you do not already have a Microsoft account, sign up for one at https://signup.live.com/. If you do not already have an Azure ML workspace, browse to http://aka.ms/edx-dat203.1x-aml and click Get Started Now. Then follow the instructions to sign up for a free Azure ML workspace. If prompted, sign in with your Microsoft account credentials. Note: Your free-tier Azure ML workspace allows you unlimited access, with some reduced capabilities compared to a full Microsoft Azure subscription. Your experiments will only run at low priority on a single processor core. As a result, you will experience some longer wait times. However, you have full access to all features of Azure ML.
Download the Lab Files All code and data files you will need are contained in a zip file. Follow these steps to download and install the lab files. 1. 2.
Download the lab files from http://aka.ms/edx-dat203.1x-labfiles. Extract the downloaded zip file to a convenient folder on your local computer.
Summary By completing the tasks in this setup guide, you have prepared you environment for the labs in this course. Now you’re ready to start learning how to build data science and machine learning solutions.
Page 1 ... A web browser and Internet connection. Create an Azure ... Now you're ready to start learning how to build data science and machine learning solutions.
Performance for SQL Based Applications. Then, if you have not already done so, ... In the Save As dialog box, save the file as plan1.sqlplan on your desktop. 6.
A Windows, Linux, or Mac OS X computer. ⢠Azure Storage Explorer. ⢠The lab files for this course. ⢠A Spark 2.0 HDInsight cluster. Note: If you have not already ...
Start Microsoft SQL Server Management Studio and connect to your database instance. 2. Click New Query, select the AdventureWorksLT database, type the ...
performed by writing code to manipulate data in R or Python, or by using some of the built-in modules ... https://cran.r-project.org/web/packages/dplyr/dplyr.pdf. ... You can also import custom R libraries that you have uploaded to Azure ML as R.
Developing SQL Databases. Lab 4 â Creating Indexes. Overview. A table named Opportunity has recently been added to the DirectMarketing schema within the database, but it has no constraints in place. In this lab, you will implement the required cons
create a new folder named iislogs in the root of your Azure Data Lake store. 4. Open the newly created iislogs folder. Then click Upload, and upload the 2008-01.txt file you viewed previously. Create a Job. Now that you have uploaded the source data
will create. The Azure ML Web service you will create is based on a dataset that you will import into. Azure ML Studio and is designed to perform an energy efficiency regression experiment. What You'll Need. To complete this lab, you will need the fo
Lab 2 â Using a U-SQL Catalog. Overview. In this lab, you will create an Azure Data Lake database that contains some tables and views for ongoing big data processing and reporting. What You'll Need. To complete the labs, you will need the following
The final Execute R/Python Script. 4. Edit the comment of the new Train Model module, and set it to Decision Forest. 5. Connect the output of the Decision Forest Regression module to the Untrained model (left) input of the new Decision Forest Train M
In this lab, you will explore and visualize the data Rosie recorded. ... you will use the Data Analysis Pack in Excel to apply some statistical functions to Rosie's.
created previously. hbase org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles. /data/storefile Stocks. 8. Wait for the MapReduce job to complete. Query the Bulk Loaded Data. 1. Enter the following command to start the HBase shell. hbase shell. 2.
videos and demonstrations in the module to learn more. 1. Search for the Evaluate Recommender module and drag it onto the canvas. Then connect the. Results dataset2 (right) output of the Split Data module to its Test dataset (left) input and connect
In this lab, you will create schemas and tables in the AdventureWorksLT database. Before starting this lab, you should view Module 1 â Designing a Normalized ...
Challenge 1: Add Constraints. You have been given the design for a ... add DEFAULT constraints to columns based on the requirements. Challenge 2: Test the ...
Data Science and Machine Learning ... A web browser and Internet connection. ... Azure ML offers a free-tier account, which you can use to complete the labs in ...
Processing Big Data with Hadoop in Azure. HDInsight. Lab 1 - Getting Started with HDInsight. Overview. In this lab, you will provision an HDInsight cluster.
Real-Time Big Data Processing with Azure. Lab 2 - Getting Started with IoT Hubs. Overview. In this lab, you will create an Azure IoT Hub and use it to collect data ...
Real-Time Big Data Processing with Azure. Lab 1 - Getting Started with Event Hubs. Overview. In this lab, you will create an Azure Event Hub and use it to collect ...
Data Science Essentials. Lab 6 â Introduction to ... modules of this course; but for the purposes of this lab, the data exploration tasks have already been ... algorithm requires all numeric features to be on a similar scale. If features are not on
Selecting the best features is essential to the optimal performance of machine learning models. Only features that contribute to ... Page 3 .... in free space to the right of the existing modules: ... Use Range Builder (all four): Unchecked.
Implementing Predictive Analytics with. Spark in Azure HDInsight. Lab 3 â Evaluating Supervised Learning Models. Overview. In this lab, you will use Spark to ...
Microsoft Azure Machine Learning (Azure ML) is a cloud-based service from Microsoft in which you can create and run data science experiments, and publish ...
A Microsoft Windows, Apple Macintosh, or Linux computer ... In this case, you must either use a Visual Studio Dev Essentials Azure account, or ... NET SDK for.
In the new browser tab that opens, note that a Jupyter notebook named ... (Raw) notebook has been created, and that it contains two cells. The first ..... Page 9 ...