We have stepped into an advanced era of machine learning, which is not a hype. ML allows building data-driven applications that learn from data and improve over time. The following statistics from Forbes highlight the contribution of machine learning to the modern business world.
The worldwide machine learning market is expected to grow from $7.3B in 2020 to $30.6B in 2024, attaining a CAGR of 43%.
$3.1B has been raised for machine learning companies with the investments of more than 4400 companies.
North America (80%) leads in ML adoption, followed by Asia (37%) and Europe (29%).
74% of data scientists and C-level executives are using ML for performance analysis and reporting.
Despite the buzz surrounding ML, a Gartner report says that almost 50% of projects fail to reach production. Successful execution of ML projects requires months of engineering investments. Fortunately, Azure Machine Learning helps expedite the journey of ML adoption for enterprises. In this blog, we will cover seven key Azure Machine Learning benefits, which will show you how Azure ML can be lucrative for your enterprise.
Azure machine learning services offer a cloud-based environment to train, deploy, manage, automate and monitor ML models across an enterprise. Azure ML supports deep learning, supervised, and unsupervised learning to deliver accurate and insightful predictions. Further, Azure ML also supports no-code or low-code options to popularize machine learning among the non-tech community.
Let’s dive deep and see the advantages of using Azure machine learning.
1. Offering Machine Learning as a Service
Machine learning as a service (MLaaS) covers any service that offers ML solutions as part of its cloud computing solutions. Small and mid-sized businesses (SMBs) prefer MLaaS due to its reliability, cost-effectiveness, and the ability to handle infrastructural issues such as data preparation, model training, and evaluation.
Azure ML comes with Microsoft Azure public cloud platform and is recognized as a prominent MLaaS provider. But it distinguishes itself from other MLaaS providers with its unique features.
Comprehensive ML support with hundreds of ML algorithms
ML for all skill levels
Azure Machine Learning APIs
Data pre-processing made easy with sample modules
The beauty of Azure ML comes with its pay-as-you-go service. Further, Azure ML allows you to build applications without having to set up complex hardware or software. You need to subscribe and use what you need, and Azure takes care of the deployment and maintenance of your ML applications.
2. Machine learning simplified with Azure ML Studio
With Azure Machine Learning Studio, ML development becomes simplified and user-friendly. Azure ML Studio is an integrated ML development product that ensures flawless ML development experience for data models, pre-processing modules, ML algorithms, and other elements. Azure ML studio comes with drag-and-drop features and an interactive design interface, making execution of training experiments, monitoring results, and linking most easy.
Azure ML Studio facilitates easy implementation of predictive models and algorithms as a web service. Easy web services deployment of ML models enables other cloud users and applications to use ML applications directly without manual help.
Working with Azure ML studio is a pleasing experience with its organized mind map format and visual connections between datasets and modules. Azure ML studio comes with a workspace environment that provides numerous sample experiments as a great starting point.
Azure ML offers a comprehensive range of machine learning algorithms, including linear regression, decision tree, clustering, logistic regression and others. Implementing ML algorithms has become very easy with the built-in drag and drop features. That said, you need to have the fundamental understanding of algorithms and data wrangling expertise to deliver the best ML models using Azure ML.
Azure ML empowers professionals with superior visualizations, thereby reducing coding requirements and streamlining the properties of algorithms. Azure ML enables importing and fine-tuning training data at ease and helps save on cost and efforts. Azure’s comprehensive collection of predictive algorithms and their drag-and-drop-based implementation is a great value proposition for sure.
4. Competitive pricing plan
Microsoft provides a classic Azure Machine Learning version and Azure ML Studio just by signing up for a Microsoft account. This basic version offers free access to Azure ML without the need for an Azure subscription and any expiration date. Other striking features include—
Max 10 GB storage space
Max 100 modules per experiment
Support for predictive web services, Python and R
The enterprise-grade standard version comes with the following benefits—
Azure subscription and SLA
Unlimited storage space--BYO
Additional support and services, such as better storage, and modules for advanced ML experiments.
5. Seamless and faster web service deployment
Another key benefit of Azure ML is that it allows quick and easy implementation of web services. Once your ML training experiment is ready, you can deploy predictive models as a web service. Drag and drop enabled data sets, algorithms, and linking ensures seamless web services implementation for predictive models.
With authorized credentials, you can access and use any web service through any connected device. Azure ML web services are class apart and preferred because:
Azure ML manages the process for you and reduces developer efforts
Azure ML ensures faster deployment of experiments
6. Azure and Cross-platform Integration
Interoperability defines the future of AI and its subsets. Azure ML services offered by the cloud allow you to access and test your models from all over the world, through any connected device, and without compromising your data security.
With a secure internet connection, you can access ML services and manage your models with Azure ML’s support for diverse programming languages, operating systems, and databases.
With Azure Machine Learning solutions, enterprises can retrieve and access their data anywhere and anytime. It enables direct data access through different sources like Azure SQL, Hive Query, on-premises data sources, and many others.
7. Comprehensive Documentation and Community Support
Last but not the least, Microsoft Azure provides comprehensive documentation with tutorials, examples, and references to help enterprises in deploying, managing, and accessing ML solutions swiftly. Also, the Azure Community Support allows users to interact with experts and get answers to specific queries.
In A Nutshell
These were seven of the most important Azure Machine Learning benefits that can propel business growth. Deploying ML solutions and managing big data has always been an intricate challenge for enterprises. But with Azure ML, building advanced ML solutions has become more simplified provided you rely on the right AI expert to get the most out of Azure ML offerings.
Attri helps you to shape your AI adoptions with relevant ML knowledge, Azure ML expertise, and leveraging Microsoft Cloud Data Platform Solutions. Being a Microsoft Azure ML consultant, we help you to plan a concrete AI roadmap backed by Azure capabilities and extract the most out of Azure Machine Learning.
Attri helps enterprises in their AI adoption journey from use case identification to PoC development to AI execution. No matter how much you have progressed with your enterprise AI adoption, Attri’s experienced resources make your AI implementation journey rewarding.
For more information on Azure Machine Learning Services from Attri, you can visit our Azure ML page.
As a former professor and publisher of technical books, Mugdha always keeps up with the latest academic and industry advances. An educator at heart, she enjoys sharing knowledge and connecting with likeminded folks.
Never miss a story
Join our growing community of 1000+ readers and get inspiring articles delivered in your inbox.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.