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Top 5 Machine Learning (MLaaS) Platforms for the Future

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Platform as a Service is one of the new and quickly evolving technologies that has taken product development to new levels. For instance, PaaS, IaaS, and SaaS technologies have changed the technological landscape in the business sector.

These services continue to grow rapidly, and at the same time, they open ways for new similar cloud services. One of these services is called Machine learning as a Service, and it’s becoming quite a competitor for other technologies in the market.

The Need For MLaaS Platforms

As businesses continue to shift their data to cloud platforms, MLaaS becomes a key player in helping them to draw useful insights. Now, capturing critical business insights isn’t too expensive, thanks to MLaaS platforms.

Typically, an MLaaS platform provides machine learning integrations to businesses. Regardless of budget and business size, these solutions are highly useful because they reduce the effort of building specialized ML solutions.

So, you no longer need special services to develop ML models that will read and analyze your company data. Now, MLaaS platforms provide these services at a relatively cheaper cost. So, you’re only paying for the MLaaS and possible cloud storage for your data.

As MLaaS platforms automatically analyze critical parameters like product reviews, customer responses, etc., they can predict possible outcomes, allowing you to make better decisions for your business.

Top MLaaS Platforms for the Future

In this post, we will talk about the best MLaaS platforms that are here to stay. So, if you’re considering shifting to such a platform, here are the options to consider:

TensorFlow

TensorFlow is a renowned name in the world of AI. It’s an open-source library featuring ML models for different applications. Interestingly, TensorFlow’s ML models were initially designed for Google’s internal operations, but they were later made available to the general public.

TensorFlow offers more flexible solutions, helping customers to develop deep neural networks through APIs and Keras libraries. It’s one of the largest hubs of ML libraries and an immensely popular tool for AI enthusiasts.

IBM Watson

IBM Watson is a comprehensive MLaaS solution for enterprise businesses. It can address the needs of large scale businesses and has a proven track record for efficient cloud-based ML services.

Its premium feature is the Watson Speech-to-Text tool that translates spoken language to text in real-time. It’s a technology unmatched, and it goes with the Watson Language Translator, another masterpiece from the tech giant.

Microsoft Azure

Azure from Microsoft provides stream analytics tools. It’s a handy option for processing large text files thanks to its vast set of pre-trained models. Moreover, there is custom analytics that can seamlessly integrate with existing systems.

It’s an incredibly fast and flexible option providing end-to-end analytics to the customers. It’s one of the reasons why Azure is such a popular MLaaS platform in the business world.

BigML

As the name suggests, BigML provides extensive ML tools to converge all your data streams to a single platform. It simplifies analysis, sharing and collaboration with the customers.

BigML is more focused on the engineering sector, providing services to the automotive, aerospace, energy sector, IoT, telecom and transportation, etc. But it also has solutions for the financial and healthcare setups.

It features pre-trained models with options to train new models with specialized classification and regression algorithms.

MonkeyLearn

MonkeyLearn primarily deals with text analysis. It has a comprehensive toolkit to analyze documents, emails, social media posts, and other content that involves text.

It provides tools like sentiment analysis, topic analysis and text extraction features, and it’s a highly scalable option for businesses.

With an easy-to-use interface, MonkeyLearn has the essential capabilities to collect, process and predict data in a visually engaging format, helping the customers to understand the data more effectively.

Conclusion

With so many MLaaS platforms out there, it’s quite convenient for modern businesses to opt for solutions that fit their needs. The abundance of these platforms is a clear indicator that Machine learning is the future of businesses belonging to any sector.

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