Welcome!

@CloudExpo Authors: Elizabeth White, Liz McMillan, Yeshim Deniz, Stackify Blog, ManageEngine IT Matters

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).

@CloudExpo Stories
New competitors, disruptive technologies, and growing expectations are pushing every business to both adopt and deliver new digital services. This ‘Digital Transformation’ demands rapid delivery and continuous iteration of new competitive services via multiple channels, which in turn demands new service delivery techniques – including DevOps. In this power panel at @DevOpsSummit 20th Cloud Expo, moderated by DevOps Conference Co-Chair Andi Mann, panelists will examine how DevOps helps to meet th...
SYS-CON Events announced today that Progress, a global leader in application development, has been named “Bronze Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Enterprises today are rapidly adopting the cloud, while continuing to retain business-critical/sensitive data inside the firewall. This is creating two separate data silos – one inside the firewall and the other outside the firewall. Cloud ISVs oft...
SYS-CON Events announced today that CollabNet, a global leader in enterprise software development, release automation and DevOps solutions, will be a Bronze Sponsor of SYS-CON's 20th International Cloud Expo®, taking place from June 6-8, 2017, at the Javits Center in New York City, NY. CollabNet offers a broad range of solutions with the mission of helping modern organizations deliver quality software at speed. The company’s latest innovation, the DevOps Lifecycle Manager (DLM), supports Value S...
As DevOps methodologies expand their reach across the enterprise, organizations face the daunting challenge of adapting related cloud strategies to ensure optimal alignment, from managing complexity to ensuring proper governance. How can culture, automation, legacy apps and even budget be reexamined to enable this ongoing shift within the modern software factory?
SYS-CON Events announced today that Cloudistics, an on-premises cloud computing company, has been named “Bronze Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Cloudistics delivers a complete public cloud experience with composable on-premises infrastructures to medium and large enterprises. Its software-defined technology natively converges network, storage, compute, virtualization, and management into a ...
SYS-CON Events announced today that Ocean9will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Ocean9 provides cloud services for Backup, Disaster Recovery (DRaaS) and instant Innovation, and redefines enterprise infrastructure with its cloud native subscription offerings for mission critical SAP workloads.
SYS-CON Events announced today that Systena America will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Systena Group has been in business for various software development and verification in Japan, US, ASEAN, and China by utilizing the knowledge we gained from all types of device development for various industries including smartphones (Android/iOS), wireless communication, security technology and IoT serv...
Multiple data types are pouring into IoT deployments. Data is coming in small packages as well as enormous files and data streams of many sizes. Widespread use of mobile devices adds to the total. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will look at the tools and environments that are being put to use in IoT deployments, as well as the team skills a modern enterprise IT shop needs to keep things running, get a handle on all this data, and deli...
We build IoT infrastructure products - when you have to integrate different devices, different systems and cloud you have to build an application to do that but we eliminate the need to build an application. Our products can integrate any device, any system, any cloud regardless of protocol," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA
DevOps is often described as a combination of technology and culture. Without both, DevOps isn't complete. However, applying the culture to outdated technology is a recipe for disaster; as response times grow and connections between teams are delayed by technology, the culture will die. A Nutanix Enterprise Cloud has many benefits that provide the needed base for a true DevOps paradigm.
SYS-CON Events announced today that Infranics will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Since 2000, Infranics has developed SysMaster Suite, which is required for the stable and efficient management of ICT infrastructure. The ICT management solution developed and provided by Infranics continues to add intelligence to the ICT infrastructure through the IMC (Infra Management Cycle) based on mathemat...
SYS-CON Events announced today that Carbonite will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Carbonite protects your entire IT footprint with the right level of protection for each workload, ensuring lower costs and dependable solutions with DoubleTake and Evault.
Internet of @ThingsExpo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with the 21st International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @ThingsExpo Silicon Valley Call for Papers is now open.
SYS-CON Events announced today that HTBase will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. HTBase (Gartner 2016 Cool Vendor) delivers a Composable IT infrastructure solution architected for agility and increased efficiency. It turns compute, storage, and fabric into fluid pools of resources that are easily composed and re-composed to meet each application’s needs. With HTBase, companies can quickly prov...
SYS-CON Events announced today that Juniper Networks (NYSE: JNPR), an industry leader in automated, scalable and secure networks, will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Juniper Networks challenges the status quo with products, solutions and services that transform the economics of networking. The company co-innovates with customers and partners to deliver automated, scalable and secure network...
SYS-CON Events announced today that Hitachi Data Systems, a wholly owned subsidiary of Hitachi LTD., will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City. Hitachi Data Systems (HDS) will be featuring the Hitachi Content Platform (HCP) portfolio. This is the industry’s only offering that allows organizations to bring together object storage, file sync and share, cloud storage gateways, and sophisticated search and...
This talk centers around how to automate best practices in a multi-/hybrid-cloud world based on our work with customers like GE, Discovery Communications and Fannie Mae. Today’s enterprises are reaping the benefits of cloud computing, but also discovering many risks and challenges. In the age of DevOps and the decentralization of IT, it’s easy to over-provision resources, forget that instances are running, or unintentionally expose vulnerabilities.
SYS-CON Events announced today that T-Mobile will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. As America's Un-carrier, T-Mobile US, Inc., is redefining the way consumers and businesses buy wireless services through leading product and service innovation. The Company's advanced nationwide 4G LTE network delivers outstanding wireless experiences to 67.4 million customers who are unwilling to compromise on ...
SYS-CON Events announced today that SoftLayer, an IBM Company, has been named “Gold Sponsor” of SYS-CON's 18th Cloud Expo, which will take place on June 7-9, 2016, at the Javits Center in New York, New York. SoftLayer, an IBM Company, provides cloud infrastructure as a service from a growing number of data centers and network points of presence around the world. SoftLayer’s customers range from Web startups to global enterprises.
The 21st International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding busin...