Welcome!

@ThingsExpo Authors: Elizabeth White, Pat Romanski, Karyn Jeffery, Kevin Sparenberg, Yeshim Deniz

Related Topics: @CloudExpo, Mobile IoT, @ThingsExpo

@CloudExpo: Blog Post

Machine Learning - Azure vs AWS By @SrinivasanSunda | @CloudExpo #IoT #Cloud

The importance of machine learning

Machine Learning - Azure vs AWS

Machine Learning, which is a process to predict future patterns and incidents based on the models created out of past data, is definitely the most important part of the success of the Internet of Things in the enterprise and consumer space. The main reason is that without machine learning the entire backbone of the Internet of Things - event acquisition, event processing , event storage and event reporting - is merely a live display of events happening elsewhere and will not provide any value to its consumers. Think of a smart monitor in an oil well that monitors various climatic conditions and other factors that can cause a failure; unless the monitor is able to predict of a failure and corrects itself the usage of such solution is quite limited.

MLPaaS - Azure Vs AWS
In that context, Machine Learning Platform as a Service (MLPaaS) has been a major component of the major cloud platforms. Both Azure and AWS have equivalent services, the below thoughts are comparison of major building blocks of a machine learning service and how the respective cloud providers handle them.

Machine Learning Component

Azure

Amazon AWS

Training Data Enablement: As the machine learning falls in to two major categories of Supervised Learning and Unsupervised Learning, proper training data is one of the most important aspect of a success of a machine learning experiment and how well a MLPaaS facilitates availability and usage of training data is a key factor.

Azure ML has extensive options for data input and manipulation. The Data sources could be any of, Hive, Azure SQL, Blob Storage, web based data feeding engines and even the data could be manually entered.

 

Never a input data from source could be directly used as a training data and hence in this context, Azure ML has an array of transformation functions like, Filter, Data Manipulation, Split and Reduce.

 

With the effective use of above options Azure ML will provide an effective means of integrating training data as part of the machine learning process.

AWS Machine Learning also supports multiple data sources within its eco system.

 

Amazon Simple Storage Service (Amazon S3) is storage for the AWS cloud platform. Amazon ML uses Amazon S3 as a

primary data repository.

 

Amazon ML allows you to create a data source object from data residing in Amazon Redshift, which is the Data Warehouse Platform as a service.

 

Amazon ML also allows you to create a datasource object from data stored in a MySQL database in Amazon

Relational Database Service (Amazon RDS).

 

Also Amazon ML provides a rich set of data transformation functions like, N-gram transformation, Orthogonal Sparse Bigram transformation and more.

Support For Machine Learning Life Cycle: Developing and consuming a machine learning model for an enterprise use case is in itself a eco system. There are multiple players like data scientist, data analyst, ETL Developers, Visualization Engineers and business users are involved and each one plays an important role. Hence any machine learning service should support this life cycle of work flow.

One of the key success factor of Azure ML is the positioning of Azure ML studio and its user friendly graphical interface and supporting workflows which makes the machine learning process highly collaborative and interactive.

The concept of Workspace nicely allows for separation of duties as well as seamless integration with rest of Azure eco system like storage. Typically Data scientist initially creates models and train them with various parameters and data combinations \. Also rich Visualization features help data scientist to test the results easily.

Once a model is trained successfully, Azure provides easy options to create a scoring experiment which can be ultimately published as a web service to be consumed by client applications.

The graphical interface of Amazon ML provides a very similar experience and features in terms of creating and training models.

 

While there is no separation between a training and scoring experiment, Amazon ML provides lot of options for model evaluation and interpretation.

 

When we evaluate an ML model, Amazon ML provides an industry-standard metric and a number of

insights to review the predictive accuracy of the model.

Algorithm Support: This is probably the most important piece of evaluating a machine learning service as there are different algorithms which can be applied for different situations.

While almost all machine learning solutions are covered under the three major categories namely, Clustering, Classification and Regression based on whether we needed a supervised machine learning or unsupervised machine learning.

However the real challenge could be the particular algorithm that suit the above 3 analysis categories.

Azure machine learning supports a whole array of algorithms be it, Decision Trees, Logistic Regression, Bayes Point Machine, Nerual Networks, K-Means ... to just name a few.

One important aspect of Azure machine learning is the democratization of these advanced algorithms that even without any programming knowledge of machine learning languages like R we could effectively deploy them for given use cases.

Amazon ML supports three types of ML models: binary classification, multiclass classification, and regression.

 

As the name indicates, Binary classification is used to predict one of two possible out comes.

 

Multi class classification is used to predict one of three or more possible out comes.

 

Regression is used to predict a continuous variable which is a number.

However as per documentation there does not seem to be an option within the Amazon ML to select individual algorithms like a K-Means as part of evaluating the model.

Consumer Applications: Once the model is trained it has to be put into the practice and the most natural usage is that the results of machine learning are to be used as part of consumer application and in todays context it is mostly a mobile based consumer. So a robust machine learning service should support multiple consumer applications too.

Azure machine learning provides ready to go client side code for the web services that are published. It supports clients for both request and response model as well as batch based execution. Azure machine learning also produces sample client side code in C#, Python and R. It provides an easy interface for testing the request and response parameters. When it comes to batch execution, Azure machine learning provides APIs for submitting and starting a job and sample code is available in C#, Python and R. With this support Azure machine learning provides excellent support for developing client side applications.

Amazon support both batch predictions as well as real time predictions with the support of API for each of the tasks.

 

Amazon ML API has batch prediction APIs like, Create, Update, Delete which can be used for creating batch applications.

 

Similarly the real time machine learning API samples are available in platforms like Java, Python and Scala.

Pricing aspects are not discussed in the table because PaaS solutions like machine learning are charged per usage and the pricing is either per prediction or by per prediction hour and typically enterprises would worry more about the capabilities of the platform in choosing a machine learning service.

Also without doing significant machine learning case studies we cannot comment on the algorithms and their support; however, a higher level view indicates that Azure Machine Learning supports more algorithms and individual choice of algorithms within a category like clustering, classification which may be of interest to seasoned data scientists. Also most data scientists predict the future of machine learning will be on unsupervised learning which has got a good support from Azure in the form clustering algorithms, especially the K-Means algorithm.

More Stories By Srinivasan Sundara Rajan

Highly passionate about utilizing Digital Technologies to enable next generation enterprise. Believes in enterprise transformation through the Natives (Cloud Native & Mobile Native).

@ThingsExpo Stories
Everything run by electricity will eventually be connected to the Internet. Get ahead of the Internet of Things revolution and join Akvelon expert and IoT industry leader, Sergey Grebnov, in his session at @ThingsExpo, for an educational dive into the world of managing your home, workplace and all the devices they contain with the power of machine-based AI and intelligent Bot services for a completely streamlined experience.
The financial services market is one of the most data-driven industries in the world, yet it’s bogged down by legacy CPU technologies that simply can’t keep up with the task of querying and visualizing billions of records. In his session at 20th Cloud Expo, Karthik Lalithraj, a Principal Solutions Architect at Kinetica, discussed how the advent of advanced in-database analytics on the GPU makes it possible to run sophisticated data science workloads on the same database that is housing the rich...
IoT is at the core or many Digital Transformation initiatives with the goal of re-inventing a company's business model. We all agree that collecting relevant IoT data will result in massive amounts of data needing to be stored. However, with the rapid development of IoT devices and ongoing business model transformation, we are not able to predict the volume and growth of IoT data. And with the lack of IoT history, traditional methods of IT and infrastructure planning based on the past do not app...
DX World EXPO, LLC., a Lighthouse Point, Florida-based startup trade show producer and the creator of "DXWorldEXPO® - Digital Transformation Conference & Expo" has announced its executive management team. The team is headed by Levent Selamoglu, who has been named CEO. "Now is the time for a truly global DX event, to bring together the leading minds from the technology world in a conversation about Digital Transformation," he said in making the announcement.
With tough new regulations coming to Europe on data privacy in May 2018, Calligo will explain why in reality the effect is global and transforms how you consider critical data. EU GDPR fundamentally rewrites the rules for cloud, Big Data and IoT. In his session at 21st Cloud Expo, Adam Ryan, Vice President and General Manager EMEA at Calligo, will examine the regulations and provide insight on how it affects technology, challenges the established rules and will usher in new levels of diligence...
In the enterprise today, connected IoT devices are everywhere – both inside and outside corporate environments. The need to identify, manage, control and secure a quickly growing web of connections and outside devices is making the already challenging task of security even more important, and onerous. In his session at @ThingsExpo, Rich Boyer, CISO and Chief Architect for Security at NTT i3, discussed new ways of thinking and the approaches needed to address the emerging challenges of security i...
Internet of @ThingsExpo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devic...
"The Striim platform is a full end-to-end streaming integration and analytics platform that is middleware that covers a lot of different use cases," explained Steve Wilkes, Founder and CTO at Striim, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
What sort of WebRTC based applications can we expect to see over the next year and beyond? One way to predict development trends is to see what sorts of applications startups are building. In his session at @ThingsExpo, Arin Sime, founder of WebRTC.ventures, discussed the current and likely future trends in WebRTC application development based on real requests for custom applications from real customers, as well as other public sources of information.
SYS-CON Events announced today that Calligo, an innovative cloud service provider offering mid-sized companies the highest levels of data privacy and security, has been named "Bronze Sponsor" of SYS-CON's 21st International Cloud Expo ®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Calligo offers unparalleled application performance guarantees, commercial flexibility and a personalised support service from its globally located cloud plat...
SYS-CON Events announced today that Massive Networks will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Massive Networks mission is simple. To help your business operate seamlessly with fast, reliable, and secure internet and network solutions. Improve your customer's experience with outstanding connections to your cloud.
SYS-CON Events announced today that DXWorldExpo has been named “Global Sponsor” of SYS-CON's 21st International Cloud Expo, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Digital Transformation is the key issue driving the global enterprise IT business. Digital Transformation is most prominent among Global 2000 enterprises and government institutions.
SYS-CON Events announced today that Datera, that offers a radically new data management architecture, has been named "Exhibitor" of SYS-CON's 21st International Cloud Expo ®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Datera is transforming the traditional datacenter model through modern cloud simplicity. The technology industry is at another major inflection point. The rise of mobile, the Internet of Things, data storage and Big...
While the focus and objectives of IoT initiatives are many and diverse, they all share a few common attributes, and one of those is the network. Commonly, that network includes the Internet, over which there isn't any real control for performance and availability. Or is there? The current state of the art for Big Data analytics, as applied to network telemetry, offers new opportunities for improving and assuring operational integrity. In his session at @ThingsExpo, Jim Frey, Vice President of S...
"We provide IoT solutions. We provide the most compatible solutions for many applications. Our solutions are industry agnostic and also protocol agnostic," explained Richard Han, Head of Sales and Marketing and Engineering at Systena America, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"DX encompasses the continuing technology revolution, and is addressing society's most important issues throughout the entire $78 trillion 21st-century global economy," said Roger Strukhoff, Conference Chair. "DX World Expo has organized these issues along 10 tracks with more than 150 of the world's top speakers coming to Istanbul to help change the world."
"We are focused on SAP running in the clouds, to make this super easy because we believe in the tremendous value of those powerful worlds - SAP and the cloud," explained Frank Stienhans, CTO of Ocean9, Inc., in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We've been engaging with a lot of customers including Panasonic, we've been involved with Cisco and now we're working with the U.S. government - the Department of Homeland Security," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"MobiDev is a Ukraine-based software development company. We do mobile development, and we're specialists in that. But we do full stack software development for entrepreneurs, for emerging companies, and for enterprise ventures," explained Alan Winters, U.S. Head of Business Development at MobiDev, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
SYS-CON Events announced today that DXWorldExpo has been named “Global Sponsor” of SYS-CON's 21st International Cloud Expo, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Digital Transformation is the key issue driving the global enterprise IT business. Digital Transformation is most prominent among Global 2000 enterprises and government institutions.