Data Science and Machine Learning Essentials Lab Setup

Overview This course includes labs that require you to conduct data science experiments in Microsoft Azure Machine Learning (Azure ML) Studio and to develop Python and R code. This setup guide describes how

to prepare for the labs.

Setup Tasks To prepare the lab environment, you must perform the following tasks: 1. Create an Azure ML account 2. Download and extract the lab files 3. Install R and RStudio or 4. Install Python Anaconda

What You’ll Need To perform the setup tasks, you will need the following:  

A Windows, Linux, or Apple Macintosh 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 course.

Sign Up for a Microsoft Account 1. If you do not already have a Microsoft account, sign up for one at https://signup.live.com/.

Sign Up for a Free Azure ML Account 1. Browse to http://bit.ly/azureml_login and click Get started now. 2. When prompted, choose the option to sign in, and sign in with your Microsoft account credentials. 3. On the Welcome page, watch the overview video if you want to see an introduction to Azure ML Studio. Then close the Welcome page by clicking the checkmark icon. Note: Your free-tier Azure ML account 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.

Install R and RStudio R is a programming language for conducting statistical analysis processes and visualizing data. You will create R code in some labs in this course. Note: In this course, you can choose to complete programming exercises in Python or R (or both). If you plan to use R, complete this procedure to install the R runtime and development tools. If you do not plan to use R, you can skip this procedure.

Install R 1. In a web browser, navigate to https://cran.r-project.org/bin/. 2. Open the folder for your operating system (Linux, MacOS, MacOSX, or Windows) and follow the instructions to install R. Note: Linux users must choose the subdirectory for the Linux type and version. Windows users with 64-bit computers can install both 32 and 64 bit versions or R. 3. Verify installation by starting R and entering a simple R expression such as 1 + 2 (which should produce the result 3) as shown in the following image.

4. Close R.

Install RStudio 1. In a web browser, navigate to https://www.rstudio.com/products/rstudio/download/. 2. Run the installer for your operating system (Windows, MacOSX, Ubuntu, or Fedora) to install RStudio. 3. To verify installation, start RStudio; which should resemble the following image:

4. If you are using Windows, ensure that RStudio is configured to use the correct version or R (32bit or 64-bit) by selecting Global Options on the Tools menu, as shown in the following image.

5. When you have verified installation and configuration, close RStudio.

Install Python Anaconda Python Anaconda is a distribution of Python that includes the Spyder Integrated Development Environment (IDE), which you will use to create Python code in the labs for this course. Note: In this course, you can choose to complete programming exercises in Python or R (or both). If you plan to use Python, complete this procedure to install the Python runtime and development tools. If you do not plan to use Python, you can skip this procedure.

Install the Python Anaconda Distribution 1. 2. 3. 4.

In a web browser, navigate to http://continuum.io/downloads. Choose the installer for your operating system (Windows, Apple Macintosh, or Linux). Complete the installation process for Python 2.7. After installation is complete, verify the installation by starting Spyder, which should look similar to the following image:

5. Close Spyder.

Download and Extract the Lab Files Each lab in this course requires sample data files and code script files that you will use to build machine learning experiments. These files are available as a zip archive in the GitHub repository for this course. 1. Download the lab files zip archive from https://github.com/MicrosoftLearning/Data-Scienceand-ML-Essentials/raw/master/Labs/Labfiles.zip. 2. Extract the downloaded archive to a folder on your 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.

Microsoft Learning Experiences - GitHub

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 ...

975KB Sizes 1 Downloads 284 Views

Recommend Documents

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
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 ...

Microsoft Learning Experiences - GitHub
Start Microsoft SQL Server Management Studio and connect to your database instance. 2. Click New Query, select the AdventureWorksLT database, type the ...

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
Developing SQL Databases. Lab 4 – 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

Microsoft Learning Experiences - GitHub
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

Microsoft Learning Experiences - GitHub
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

Microsoft Learning Experiences - GitHub
Lab 2 – 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

Microsoft Learning Experiences - GitHub
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

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
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

Microsoft Learning Experiences - GitHub
In this lab, you will create schemas and tables in the AdventureWorksLT database. Before starting this lab, you should view Module 1 – Designing a Normalized ...

Microsoft Learning Experiences - GitHub
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 ...

Microsoft Learning Experiences - GitHub
Processing Big Data with Hadoop in Azure. HDInsight. Lab 1 - Getting Started with HDInsight. Overview. In this lab, you will provision an HDInsight cluster.

Microsoft Learning Experiences - GitHub
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 ...

Microsoft Learning Experiences - GitHub
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 ...

Microsoft Learning Experiences - GitHub
Data Science Essentials. Lab 6 – 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

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
Implementing Predictive Analytics with. Spark in Azure HDInsight. Lab 3 – Evaluating Supervised Learning Models. Overview. In this lab, you will use Spark to ...

Microsoft Learning Experiences - GitHub
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 ...

Microsoft Learning Experiences - GitHub
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.

Microsoft Learning Experiences - GitHub
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 ...