The development of a product into full-fledged service(s) on cloud has seen the rise of new services such as Platform as a service (PaaS), Infrastructure as a service (IaaS) and Software as a service (SaaS). Their growth as a market has led to a battle in the cloud space market. Joining these cloud-based services and slowly opening up another competition is Machine Learning as a service (MLaaS). The growing trend of shifting data storage to cloud, maintaining it and deriving the best insights from it has found an ally in MLaaS which provides these solutions at a reduced cost.
What Is MLaaS ?
Machine learning as a service (MLaaS) is an array of services that provide machine learning tools as part of cloud computing services. MLaaS helps clients benefit from machine learning without the cognate cost, time and risk of establishing an inhouse internal machine learning team. Infrastructural concerns such as data pre-processing, model training, model evaluation, and ultimately, predictions, can be mitigated through MLaaS.
Service providers offer tools such as predictive analytics and deep learning, APIs, data visualisation, natural language processing and more. The computation aspect is handled by the service provider's data centers.
How MLaaS Functions:
Simply put, MLaaS is a set of services that offer ready-made, slightly generic machine learning tools that can be adapted by any organisation as a part of their working needs. These services range from data visualisation, a slew of application programming interfaces, facial recognition, natural language processing, predictive analytics and deep learning, among others. The MLaaS algorithms are used to find pattern in data. Mathematical models are built using these patterns and the models are used to make predictions using new data.
The key is in the fact that the users (in this case, organisations who purchase MLaaS) do not need to handle the actual computation. The providers' data centres manage it remotely. MLaaS is also the only full-stack AI platform that consolidates systems ranging from mobile application, enterprise information, industrial automation and control, as well as advanced sensors such as LiDar, among others.
MLaaS is a platform that provides both pattern recognition and probabilistic reasoning. This provides thorough and sound ML solution that provides the flexibility of using different methods to create customised workflow specifically to meet the company's needs.
MLaaS are supported by algorithms such as convolutional neural network (CNN), deep neural networks (DNN), Bayesian networks, probabilistic graphical models, Restricted Boltzmann machine (RBM) and pattern recognition, among others.
Many cloud providers including Microsoft, Amazon and IBM, among others, offer MLaaS tools.