MLaaS (Machine Learning as a Service): What You Need To Know
Machine Learning has been one of the most rapidly growing domains in information technology and has found applications in almost every industry that you can think of. Wherever there is data, Machine Learning is involved, and it is not a hidden fact anymore that Machine Learning can help you do wonders with data mining and data management. With the world generating a gazillion bytes of data every hour, it is almost next to impossible to calculate that data without the help of Machine Learning, and when you combine the accessibility of cloud computing with the efficiency of Machine Learning, the possibilities become endless.
Machine Learning as a Service or MLaaS is the domain of cloud computing that provides Machine Learning tools to make it more effective and efficient. You might be familiar with a lot of such platforms that you use in your daily life but never realize that they are working with Machine Learning. Take the biggest example in front of you, YouTube! Ever wondered how you start with an educational video and end up with a video of cats fighting relentlessly?
Those recommendations that you get, the videos that you watch in your auto playlist, every single one of them is due to the Machine Learning algorithms that YouTube uses to analyze your patterns and preferences. Isn’t it amazing? Well, this is just the tip of the iceberg of services that Machine Learning offers, and in this article, we are going to take a deeper dive into the ocean of innovations that Machine Learning as a Service (MLaaS) is, so make sure you read it till the end.
What Is The Use Of MLaaS? Understanding The Motive Behind
With the increasing demand and usage of Machine Learning in the industry, almost every other person wants to include Machine Learning algorithms in their business to gain better insights into their potential audiences. To help such people with easy-to-use Machine Learning solutions and to attract them toward their cloud platforms, many industry giants have deployed cloud platforms with Machine Learning tools included with their cloud services to make them more accessible to the masses. This idea gave birth to Machine Learning as a service or MLaaS.
Machine Learning as a Service is a cloud platform integrated with the services of cloud computing. This combination helps the clients instantly get started with the basics of Machine Learning with the help of easy-to-use tools that are user-friendly and easy to interact with. All the calculations and processing are done via the back end by the provider only. This helps the user to not only understand the latest data trends but they can also make the most out of unprocessed data to yield better results.
These cloud platforms offer many Machine Learning tools for various processes, such as predictive analysis, data transformation, advanced text analysis, data visualization, etc. All these tools can be very helpful for an organization if they specifically deal in a domain in which they get hands-on with a lot of data.
The main motive behind implementing Machine Learning as a Service can be summed up in the following points:
- To make Machine Learning tools accessible and easy to use
- To allow businesses to make the most out of their data
- To attract businesses to shift their workings on cloud platforms
- To lower the operational costs of small businesses by introducing them to easy-to-use Machine Learning tools
- To save the time of developers, in MLaaS they don’t have to deal with model training and evaluation
- To help large organizations sort out their data if they are already dealing in Big Data
The list can go on and on and on. Machine Learning as a Service has opened up many doors of innovations and use cases for every type of business owner to help them grow more rapidly; and, believe it or not, if you know how to handle the data, then there is almost nothing that can stop you from reaching heights you can’t imagine. The opportunities are endless.
Which Are the Most Commonly Used MLaaS Platforms And Why?
Machine Learning as a Platform has been an emerging domain in the field of technology and almost every industry giant has tried its hands at it. Some of the most used Machine Learning as a Service platforms are Amazon’s AWS MLaaS, Google’s Cloud Machine Learning Engine, and Microsoft’s Azure Machine Learning. While all the platforms are different in terms of usage and accessibility, all of them work on the same principle (i.e., making Machine Learning accessible to the masses). All of these services are affordable and highly effective when used efficiently.
To understand what makes them different and similar, let’s take a look at the top 3 types of MLaaS platforms and identify them according to a user’s requirements and perspective.
1. Amazon Machine Learning (Integrated With AWS)
This platform is a multifunctional platform that offers almost every Machine Learning tool that can be of use to a customer; however, there are some drawbacks of this platform. The automation process of this platform has some major shortcomings which make it more of a complicated Machine Learning tool. Amazon Web Services or AWS is one of the most used cloud platforms, and the good thing about Amazon Machine Learning services is that it can help you complete your tasks in no time, as the processing is quite efficient thanks to the vast cloud infrastructure. You must keep in mind that it is a paid service.
2. Microsoft Azure Machine Learning
Another big player in the industry of Machine Learning as a Service is the global leader of computing and technology, Microsoft. Microsoft’s Azure Machine Learning is one of the only platforms that gives its users total manual control on almost every Machine Learning tool, which makes it even better to gain results for clients. It is also sometimes complicated for new users as they are not familiar with the do’s and don’ts of this platform. One of the major advantages that you can get if you are working on Azure is the availability of tremendous amounts of Machine Learning solutions that are stored and ready to be accessed in the Cortana Intelligence Gallery. Microsoft offers both free and paid versions of their platform, so it is suggested that if you are a beginner you must try this out.
3. Google Cloud Machine Learning Engine CMLE
You have to be living under a rock if you are not familiar with the reach and power of Google in today’s world. Google has been the giant in almost every field of technology, and it is not behind in Machine Learning. The CMLE is Google’s brainchild, which has not only simplified the usage of Machine Learning for the common user but has also provided some of the advanced features that can help you grow your business.
The training and prediction services of CMLE are reliable and can be used together or even separately. Some of the most interesting features that CMLE offers are portable models that can be easily downloaded; use of distributed training, which means that if the data is too complex to be handled by a single machine, you can easily launch a multiple machine environment to complete it; and HyperTune, which helps you automate the process of tuning the deep learning parameters so that the results that are needed can be acquired much faster.
These are the most used platforms of MLaaS; however, platforms such as BigML, PredictionIO, IBM Watson, Tensor Flow, etc., are also some great platforms to begin your Machine Learning journey. The main reason for using all these platforms is to ensure that no shred of data is wasted and every possible insight about the customer, which can help design products and campaigns better, can be collected.
Future Of Machine Learning as a Platform: Final Verdict
As you might have understood by now, MLaaS is here to stay for the long term. While we are in the transition of becoming a hybrid generation from a smart one, we can already see that Machine Learning and Artificial Intelligence have drastically taken over our lives. From a simple smartphone to a complicated neural engine, anything and everything can be made better with the help of Machine Learning and its applications. With the amount of data that is out there due to social media usage and multiple other factors, it is possible to tell everything about a person just by analyzing their virtual habits and how they use the internet.
Machine Learning as a Platform can help manufacturers and business owners to analyze the response of their customers so that they can make amends in their product lines as well as targeting campaigns. It is truly unreal to believe that now business owners will be able to serve common people by understanding what their customers exactly want, which will not only help them make their services better will also help the consumer in getting better goods and services.
The future of Machine Learning is bright, and if you are a business that runs on the fuel of data and consumerism then, believe it or not, Machine Learning as a Platform can be a game-changer for you. Hope you found this article helpful and informational. Thank you for reading.