The original Cloud services include three different segments. Infrastructure as a service (IaaS), Platform as a service (PaaS) and Software as a Service (SaaS). In the recent times, we have seen other types of services, like Visibility as a Service (VaaS), where the customers are provided visibility to the type of traffic accessing the cloud servers and details about the traffic. This is very critical because of the inherent inability in the cloud infrastructure to provide the visibility. Now, the wave of Machine Learningand Artificial Intelligence has taken Cloud computing too. Many Cloud service providers are launching new services in Machine Learning as a Service.
What is Machine Learning as a Service (MLaaS)?
Often if your business needs Machine Learning solutions, the first thought is to build a team of ML skilled professionals and give them necessary resources to complete the task. However, if your business only needs ML solutions for a particular time and not longer having a team and running the equipment in house would cost more. That is why MLaaS can provide you the flexibility to avail the services as long as you need and as extensive as you require.
It basically provides the users with some generic ML operations, like Natural Language Processing, Deep Learning, Predictive Analysis API’s and more to make the developers life easy. They don’t have to train the data and evaluate, and the company does not have to buy the storage and computing power, because both of them come with MLaaS. If your main business does not depend on the ML solutions and only a part of it is dependent this is the best way you can invest your money for higher ROI.
What are some of the advantages of MLaaS?
The MLaaS package includes the following ML operations: Regression, Classification, Clustering, Anomaly Detection, Recommendation, Ranking, Graphical Interface and more. For many of the starters in ML, this may seem daunting to setup but compared to the stand-alone ML team at your office this is much less scarier and also you will have a lot of support from your cloud service providers.
These are some of the best MLaaS providers you can watch out for: BigML, AWS ML, Google ML, and Google Prediction API. Azure Machine Learning and Google Tensor Flow are also some of the options available on the table.
These services vary in difficulty level and some of them are mostly automated and some depend highly on the developer. In any case, you need a ML professional in your office, but he/she doesn’t have to be experienced. Also, you don’t have to run a team of 20 employees to get the work done. Since most of it is automated it will take less time to obtain the results.
These MLaaS platforms provide free as well as subscription-based plans and you can upgrade to any new plan without much fuzz. This is one of the main advantages with the Cloud platforms. If your company already used Cloud services in other areas, you can easily pull the data from those clouds and process that data. If not, it is not that hard to transfer your data into the cloud but the results more optimized if you are already working in a cloud platform!