Machine Learning Algorithm Cheat Sheet:


If you’re getting started with Data Science & Machine Learning then I think this would be a great resource for you. This “cheat sheet” helps you select the “algorithm” to test depending on the problem you are trying to solve and the data-set that you have.

Download link: (Courtesy: Azure Machine Learning)

Also, even though the cheat sheet was created to help you with “Azure Machine learning” product, it’s still valid if you use other machine learning tools.

Azure Machine Learning Algorithm Cheat Sheet


News from PASS Summit’14 for Business Analytics Professionals: #sqlpass #summit14


This post is a quick summary for all Business Analytics related updates that I saw at PASS Summit’14:

1. Theme of the Keynote(s)/Session(s) seemed to be around educating the community about the benefits of the NEW(er) tools. I saw demos/material for cloud-based tools like SQL databases, Azure stream analytics, Azure DocumentDB, AzureHDInsight & Azure Machine learning. The core message was pretty clear: A data professional does two things – 1) Guards data OR 2) helps to generate Insights from Data – And they will need to keep up-to-date on the new tools to future-proof their career.

Read more about this here:

2. Coming soon: Power BI will be able to connect to on-premise SSAS data sources (multi-dim & tabular).

3. Coming soon: A better experience to create Power BI dashboards.

Read more about Power BI updates here:

4. Azure Machine Learning adds a free-tier! You won’t need a credit-card/subscription to sign up for this.

5. I also saw sessions proposing new way of thinking about an architecture for “Self Service BI” and “Big Data” which might be worth following because since these are newer tools, it’s definitely worth considering an architecture that’s designed to make the most of the investments in these new tools. That’s it & I’ll leave you with a quote from James Phillips from Day 1’s keynote:

PASS Business Analytics VC: Insider’s Introduction to Microsoft Azure Machine Learning (#AzureML). #sqlpass



Session Abstract:
Microsoft has introduced a new technology for developing analytics applications in the cloud. The presenter has an insider’s perspective, having actively provided feedback to the Microsoft team which has been developing this technology over the past 2 years. This session will 1) provide an introduction to the Azure technology including licensing, 2) provide demos of using R version 3 with AzureML, and 3) provide best practices for developing applications with Azure Machine Learning.
Speaker BIO:
Mark is a consultant who provides enterprise data science analytics advice and solutions. He uses Microsoft Azure Machine Learning, Microsoft SQL Server Data Mining, SAS, SPSS, R, and Hadoop (among other tools). He works with Microsoft Business Intelligence (SSAS, SSIS, SSRS, SharePoint, Power BI, .NET). He is a SQL Server MVP and has a research doctorate (PhD) from Georgia Tech.


Hope to see you there!

Paras Doshi
Business Analytics Virtual Chapter’s Co-Leader


Back to basics: Multi Class Classification vs Two class classification.


Classification algorithms are commonly used to build predictive models. Here’s what they do (simplified!):

Machine Learning Predictive Algorithms analytics Introduction

Now, here’s the difference between Multi Class and Two Class:

if your Test Data needs to be classified into two classes then you use a two-class classification model.


1. Is it going to Rain today? YES or NO

2. Will the buyer renew his soon-to-expire subscription? YES or NO

3. What is the sentiment of this text? Positive OR Negative

As you can see from above examples the test data needs to be classified in two classes.

Now, look at example #3 – What is the sentiment of the text? What if you also want an additional class called “neutral” – so now there are three classes and we’ll need to use a multi-class classification model. So, If your test data needs to be classified into more than two classes then you use a multi-class classification model.


1. Sentiment analysis of customer reviews? Positive, Negative, Neutral

2. What is the weather prediction for today? Sunny, Cloudy, Rainy, Snow

I hope the examples helped, so next time you have to choose between multi class and two class classification models, ask yourself – does the problem ask you to predict two classes or more? based on that, you’ll need to pick your model.

Example: Azure Machine Learning (AzureML) studio’s classifier list:

Azure Machine Learning classifiers list

I hope this helps!

Join #SQLPASS virtual chapters for free online #SQLServer learning!


SQLPASS virtual chapters (VC) provides free sqlserver training year-round:

If you are not signed up already, then consider signing up! With that, And here’s a Quick walk-through on how to Join a VC:

If you do not have a SQLPASS account:

a. Go to

b. Fill up the required information and register

Now, After successful login/registration:

a. Go to

b. switch to MyChapters section

c. Now under virtual chapters, you would see a list of virtual chapters. Join the one’s you are interested in!

my PASS my Chapter Azure VC

Azure PASS VC Next meeting: Kung Fu Migration to Windows Azure SQL Database


Azure PASS VC’s next meeting:

Kung Fu Migration to Windows Azure SQL Database

Speaker: Scott Klein, Technical Evangelist Microsoft

Summary: As cloud computing becomes more popular and cloud-based solutions the norm rather than the fringe, the need to efficiently migrate your database is crucial. This demo-filled session will discuss the tips and tricks, methods and strategies for migrating your on-premises SQL Server databases to Windows Azure SQL Database, AKA SQL Azure. Focusing primarily on SQL Server Data Tools and the DAC Framework, this session will focus on how these tools can make you a kung-fu migration master.

About Scott: Scott Klein is a Corporate Technical Evangelist for Microsoft focusing on Windows Azure SQL Database (AKA SQL Azure) and related cloud-ready data services. His entire career has been built around SQL Server, working with SQL Server since the 4.2 days. Prior to Microsoft he was a SQL Server MVP for several years, then followed that up by being one of the first 4 SQL Azure MVPs. Scott is the author of over ½ dozen books for both WROX and APress, including Pro SQL Azure. He can be found talking about Windows Azure SQL Database and database scalability and performance at events large and small wherever he can get people to listen, such as SQL Saturday events, local SQL Server user groups, and TechEd.

Details at

Download the calendar file:

How to Join Azure PASS VC’s?

If you want to stay updated on meeting announcements, please consider registering on PASS’s website and Joining our VC:

If you do not have a SQLPASS account:

a. Go to

b. Fill up the required information and register

Now, After successful login/registration – Go to

a. switch to MyChapters section

b. Now under virtual chapters, you would see a list of virtual chapters. Join the one’s you are interested in!

my PASS my Chapter Azure VC

I look forward to seeing you at next Azure PASS VC’s meeting!

Hadoop on Azure’s Javascript Interactive Console has basic graphing functions:


The Hadoop on Azure’s Javascript console has basic graphing functions: Bar, Line & Chart. I think this is great becuase it gives an opportunity to visualize data that’s in HDFS directly from the Interactive Javascript Console! Here’s a screenshot:

hadoop on azure bar and line graph javascript

In the console, I ran the help(“graph”) command to see how I can use this function:
Draw a graph of data, options) Bar graph
graph.line(data, options) Line graph
graph.pie(data, options) Pie chart

data (array) Array of data objects
options (object) Options object, with
x (string) Property to use for x-axis values
y (string) Property to use for y-axis values
title (string) Graph title
orientation (number) x-axis label orientation in degrees
tickInterval (number) x-axis tick interval


In this blog-post, I posted that Hadoop on Azure’s Javascript Interactive Console has basic graphing functions.

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