Home » Machine Learning as a Service: Platforms that Promise to Change the World

Machine Learning as a Service: Platforms that Promise to Change the World

4. BigML

This service was developed to satisfy the needs of each user. As a result, BigML covers a lot of aspects. For example, there is a wide range of prices along with good documentation. 

BigML offers a lot of robustly-engineered ML algorithms that are able to solve problems of the real world. 

The developers tend to use this machine learning as a service platform for basket analysis, predictive maintenance, and more. The service provides opportunities to use ready-made scripts.

This platform provides various predictive applications for such industries as aerospace, energy, entertainment, financial services, food, Internet of Things or IoT, transportation, and so on. 

5. PredictionIO

If you need to be responsible for your machine learning deployment, this service is a perfect choice for you. PredictionIO is an open source server that provides developers with an opportunity to build predictive engines. 

Apache PredictionIO is an open source ML service that allows software developers as well as data scientists to build predictive engines for any ML task. For example, using PredictionIO you can do the following:

  • Create and deploy an engine as a web service fast;
  • Respond to dynamic queries;
  • Evaluate and tune several engines at the same time;
  • Speed up ML modeling;
  • and others. 

Moreover, PredictionIO has SDKs for a lot of programming languages such as Java, Ruby, PHP, Python, and so on.

6. IBM Watson

IBM has several capabilities that can assist the developers. For example, this platform is able to visualize data and describe how various data values interact with each other. 

IBM Watson was created to bring automated predictive analytics and cognitive capabilities. The service fits data scientists as well as users with no technical background.

The platform is constantly developing and starts to offer more and more interesting use cases. For example, the service allows speeding up the development process due to the automation of model training.

7. TensorFlow

TensorFlow is an end-to-end open source machine learning platform. This platform tends to assist software engineers in developing and training machine learning models. TensorFlow claims that the platform is perfect for both — experts and beginners.

This machine learning platform provides a lot of tools, libraries, and community resources that allows to create and deploy ML application easily. Moreover, the service provides guides that show the workflows for text classification as well as describe steps to train and evaluate a model. 

A lot of enterprises have chosen to use TensorFlow. For example, Airbnb, Coca-Cola, Twitter, and so on.

Choosing the Data Storage Solution

Looking for appropriate storage for collecting information and processing it can be a challenging task. However, you can utilize such databases as NoSQL and SQL. A lot of solutions (e.g. Amazon S3, Cassandra) support this combination.

Machine learning platforms allow making these processes easier. You can use the same provider for both — data storage and machine learning. Choosing this way, you can avoid problems with adjusting a data source. However, there are some platforms that offer integration with third-party tools.

Applications that Use Machine Learning

There are apps that have already integrated machine learning. So, let’s discuss them more precisely.


Snapchat is popular among millions of users and utilizes machine learning to add more fun to snaps. Let’s discuss an example. Snapchat provides users with different filters. They are able to track people’s faces correctly and add such things as glasses, hats, and more. 

For humans, it seems easy to recognize the face but it’s a complex task for machines. So, the algorithm behind this feature has been taught to recognize not only faces but also facial characteristics. 


One more wide-spread application also uses machine learning. Of course, this platform provides the users with the same facial recognition as Snapchat does but there is one more interesting use case. This application uses artificial intelligence in order to block spam messages along with offensive comments. Instagram’s users can turn this feature on or off. 

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