Nowadays Machine Learning is among the most talked about topics in the technology community.
Machine Learning is currently applied almost everywhere. It results in the emergence of ways of Machine Learning interop into quite every app. But what is Machine Learning?
It is the means of future projections on the basis of past data. Generally, ML predicts and draws an inference on the basis of data analyzed. Its algorithms should be used in compliance with challenge nature and should be trained by past data.
Almost every challenge can be solved with the help of suitable software. And the core value of ML technology is that it solves data processing problems that can’t be easily addressed by a man. Online translators are the example of such a case – although the translations are not always correct, generally, they meet people’s needs of understanding the information. Another example of ML indispensability is when people try to find the best item of goods among thousands of offers where smart applications save people’s time and help to find the best option.
The great news is you don’t have to spend years to develop Machine Learning models. There are many enterprises that offer off-the-peg API products you can integrate to an app to solve the majority of the ML challenges.
Now let’s review some of the most popular Machine Learning APIs
Integration of source of data into a model on Amazon ML
The company proposes a cloud service that it uses for any kind of projections (like fraud screening).
It is compliant with SDKs for Java, .NET, Python, PHP, Node.js, and Ruby. All the necessary docs are provided by the company but they can be a bit hard to understand for a non-expert in Data Science. If necessary, the solution can be enlarged to formulate multiple projections in real-time.
This API collects $0.42 per hour during the data processing and model generation. Later if you buy a pack of services you will pay less than a dollar per projections.
Azure Machine Learning is a cloud solution that allows building and using complex models of Machine Learning in a simple form. It also provides a set of algorithms for work.
The core element of Microsoft Azure ML is the platform ML Studio that generates modular solutions. Except for the necessary docs, a number of examples of Microsoft Azure ML applications are provided.
The prices for the usage of Microsoft Azure ML are favorable - the fixed price of $9.99 per a working place and a couple of dollars per Studio experiments and a list of other operations.
Google, like its rivals, proposes a very developer-friendly cloud-based ML solution you may take advantage of. The users of this product are provided with practical guidelines where guides on models development and the principles of API work are explained in simple for beginners.
100 projections, 5 megabytes of data trained and several thousands of projections are provided for free. If you are going to take advantage of all the functions of this API you will have to pay $10 monthly and additional fees for particular operations.
BigML model toolbar. This model proposes user-friendly ML API suitable both for amateurs and big companies and is provided by all the necessary docs describing the complete process of model development. There are works and scripts of other developers on open access that may help non-programmers to use BigML. It also provides Machine Learning services for corporate entities.
There are two types of payments that BigML presupposes - you pay for a chosen subscription or you pay on a “pay as you go” basis.
When you use the services of software engineers you’d prefer to monitor the processes of ML development regarding your task. PredictionIO represents an open-source code to create models for predictions.
PredictionIO provides software development toolkits for Java (and Android), PHP, Python, and other platforms. You may also find a number of examples for various sorts of challenges that will help you to start.
Like PredictionIO, AlchemyAPI was just a budding company that was bought by a major company. IBM acquired AlchemyAPI intending to structure its solutions into Watson. But the original version of API is still on open access.
AlchemyData News API and Visual Recognition API are the products of AlchemyAPI the first one of each offers solutions for analysis of mass communication - this means that daily this API processes about 300 thousand of articles on the Internet written in English and a user may directly use this API to find the necessary things without wasting time, falling by that outside the scope of search by catchwords.
More than 200 images may be filtered daily with the help of Visual Recognition API. It also allows the training of user’s filters free of charge. But a user will have to pay after performing such operations as facial recognition or filtration of images and so on. It is possible to take advantage of some of the functions free of charge until July so it’s time to “taste” it as soon as possible.
There are a great number of solutions that may facilitate the process of application creation and meet the needs of a developer. We’ve listed only some of them that we’ve tested and a few popular variants while there are so many other products available on the market. If you have experience using other ML APIs in your apps will be happy to hear your impressions.
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