Beginner’s Guide on Machine Learning as a Service and MLaaS Platforms
Learn more about Machine Learning as a Service (MLaaS) and its platforms
Cutting-edge technologies such as artificial intelligence and machine learning have provided immense help to businesses generate meaningful and in-depth insights efficiently and effectively. ML models are known for collecting enormous volumes of real-time data to generate useful insights without any potential error. Machine learning technology has created another technology like SaaS or PaaS known as MLaaS (Machine learning as a service) that can be conscripted from another business seamlessly. There are multiple MLaaS platforms for automatically analysing different functionalities with ML models. Let’s dig deep for gaining a strong understanding of machine learning as a service as well as features of MLaaS platforms.
Machine Learning as a Service
Machine learning as a service is a technical term to define a set of cloud computing-based tools to support data scientists and the field of data science to transform the work environment through digital transformation. MLaaS offers to automate the deployment process and help human employees with multiple ML models and MLaaS platforms. Machine learning as a Service helps companies start with machine learning without installing any software for cloud service. ML models that are integrated with MLaaSprovide a complete access to machine learning algorithms, predictive analytics, and many other tools. MLaaS is well-known for offering a trial period to make a smart decision before using MLaaS platforms.
Developers prefer to use machine learning as a service for the access to pre-built ML models with extensive resources. They reap the offers that MLaaS is popular for providing such as NLP, AI platforms, computer vision, and multiple ML APIs for businesses. There are four key players in the global machine learning as a service market— Amazon ML, Microsoft Azure machine learning, Google cloud machine learning, and IBM Watson machine learning.
There are multiple benefits of MLaaS platforms in the tech-driven market such as fast compute options, independence from building in-house infrastructure from the beginning, cost-efficient, deploying ML models outside a company, analysing online reviews, managing customer emails, enhancing product capabilities, efficient business operations, making smarter and precise business strategies, and many more. The global MLaaS market is expected to hit US$8.4 billion in 2026 for its smart functionalities.
