Top 5 Machine Learning-as-a-Service providers
Machine learning is the next big thing in computing; are you ready for it? Hiring data scientists or ML experts isn’t easy or cheap. But the rise of machine learning-as-a-service (MLaaS) suggests that you won’t need to. Today, we take a look at five of the top machine learning service providers to see which one works the best for you.
The future is looking good for machine learning. As data becomes cheaper and processing power gets even better, feats of data science become possible for everyone. Even cucumber farmers.
However, hiring machine learning experts is something of an issue, as the demand continues to outstrip the supply. What’s more, hiring a ML expert isn’t cheap, as they regularly command some of the highest salaries in tech.
Enter machine learning as a service (MLaaS). Much like other –aaS offers, MLaaS provides users with a range of tools as part of a cloud computing service. This can include tools for data visualization, facial recognition, natural language processing, image recognition, predictive analytics, and deep learning.
In the case of MLaaS, the provider handles the actual computations in their own data centers. The customers do not have to install their own software or run their own servers. Generally, the first hit is free with ML services for developers so they can evaluate a platform’s usefulness before subscribing.
MLaaS is a pretty good midway point for companies that want to dip their toes into the machine learning trend without diving right in. Having an established provider is an excellent way to help minimize any transitional issues and gives a certain surety to the whole proceedings. In any case, most of the big names in tech have their own MLaaS platform service.
Let’s take a closer look, shall we? In no particular order:
Microsoft Azure has a whole host of services available for the developer in need. But their machine learning offerings are particularly useful. Azure boasts scalable machine learning, for all sizes. They’re suitable for AI beginners and experts alike, with a range of tools that tend to be more flexible for out-of-the-box algorithms.
The main MLaaS from Microsoft Azure is the ML Studio. It has something of a steep learning curve, since almost all operations must be completed manually, from data exploration, preprocessing, choosing methods, and validating modeling results. However, to make things easier, the browser-based environment is highly simplified with a visual drag-and-drop mechanism. No coding is necessary here!
ML Studio has a huge variety of algorithms at your disposal, with around 100 methods for developers to play with. Additionally, the Cortana Intelligence Gallery is a community based collection of ML solutions used by data scientists.
ML Studio’s most popular option is the free workspace, which only requires a Microsoft account of some kind. This includes free access that never expires, 10GB of storage, R and Python support, and predictive web services. The standard enterprise grade workspace is a little pricier, with $9.90/month and a Azure subscription, but it has a lot more support and services available.
Amazon Web Services have more or less revolutionized the SaaS field. It’s no surprise that they are also a dominant player in the MLaaS department as well. Amazon Machine Learning is an incredibly popular service that guides users through creating ML models without needing to learn the complex algorithms themselves. Once you’ve created you models with the visualization tools and wizards, simple APIs create predictions for your application without any need for generating code or managing infrastructure.
There’s a high level of automation available with Amazon Machine Learning, making it useful for beginners. The service can load data from multiple sources, including Amazon RDS, Amazon Redshift, CSV files, and more.
