10 Machine Learning APIs You Should Learn

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Machine learning is everywhere nowadays, from the photographs in your phone to the filtering system on your email Inbox. Machine learning has become one of the very key components of the future. With the tendency of the net becoming more personalized, machine learning has become more important now than ever. Even big companies like Amazon use machine learning algorithms to provide you with recommendations based on your own interests.

About a decade ago, that the main intention of the net was to provide you with advice -- one keyword would generate results from around the globe on that particular keyword. But now, the focus is to supply users with more pertinent information -- something which is closer to what they are looking for. This is where machine learning plays a big part.

At this time, machine learning is dominated by big companies such as Google, Amazon, IBM, Microsoft, but the trend is now shifting and smaller businesses are bringing their algorithms and APIs to the field. APIs are making it easier for companies to share knowledge and information across multiple spectrums. Before we delve into some innovative machine learning APIs, let us take a peek at what an API actually is.

What's an API?

An API, or an Application Programming Interface, is, in the simplest terms, a code snippet that lets two software programs to communicate with one another. It is a set of definitions, protocols, and tools for building software. An API is the link between two applications, and it's responsible for sending requests from 1 program to another, in addition to returning the request.

An API is made up of two components -- a specification which describes how information is exchanged between programs and as an application interface written to that specification and published in some way for use.

There are three Kinds of APIs:

Neighborhood APIs -- All these APIs Provide OS or middleware solutions to application programs, for example Microsoft's.NET APIs.

Internet APIs -- These APIs work upon the World Wide Web to send and receive info. These include URLs.

App APIs -- These are based on Remote Procedure Call engineering a remote program part appear to be nearby to the rest of the computer software.

10 Trending Machine Learning APIs We Think You Have To Learn in 2019:

1. PredictionIO

PredictionIO is an open-source software learning API that's constructed on Apache that makes it simpler for data scientists to build predictive machines. It can be easily bundled with Apache Spark, MLlib, HBase, Elasticsearch, and Spray. It uses a unique template system for creating machine learning systems that make it simpler for programmers to customize the search engine according to their own needs.

PredictionIO may also automatically assess a forecast engine to determine the best hyperparameters to use. This amazing API takes on the significant task, allowing programmers to just add their own customization to the mixture. PredictionIO offers features such as quick build and deployment of a motor, customizable templates, and respond to dynamic questions in real-time, quicker machine learning modeling using systematic processes, pre-built evaluation measures, easy data infrastructure management, etc.. You can also contact API testing services to know more about the API tools.

2. Geneea Natural Language Processing API

Geneea is a natural language processing API that could perform analyses on raw information supplied. This API can perform analyses on data like raw text, either on the text extracted from the specified URL, or directly from the supplied document. Developers may also supply additional data, such as speech used, particular domain, etc. that will make the results more exact. Geneea performs analyses on topics such as language, correction, diacritization, tagging, topic detection, title entity recognition, etc..

3. IBM Watson Visual Recognition

IBM Watson's Visual Recognition API utilizes machine learning algorithms to properly identify, classify, and label objects. In addition, it can be used to search for visual content like colour, find human faces, tag an image, approximate age and gender, and also find similar images in a collection. Developers can even create and train customized classifiers to identify items they require. The IBM Visual Recognition is part of the larger IBM Watson Developer Cloud package of APIs which also includes speech to text, text to speech, question and response, personality insights, tone analyzer, etc..

4. Slack API

Slack became among the most popular office communication tools a few years back, and since then, it has introduced its own API to allow developers to build their own customized communication system for their workspace. This RESTful API permits developers to understand and utilize the Slack codes. It offers Slack's powerful natural language processing functionality, which enables developers to build applications that integrate with Slack, for example intelligent chatbots or other bots that could schedule meetings.

5. AT&T Speech

AT&T Speech API permits developers to integrate speech-recognition capabilities to their applications. The API is powered by the AT&T Watson address engine and also includes Natural Language Processing features like natural language understanding, speech recognition, speech transcription, and many more. It can easily transcribe a spoken phrase file to text. The API can be tuned to fit specific needs like Search, Business Search, Voicemail, SMS, Question and Answer, etc..

6. Microsoft Cognitive Service -- Text Analysis

Microsoft has been making strides when it comes to machine learning. This hot API permits developers to automatically discover that language of the text before distributing it. It can also extract information from your text including speech along with the sentiment behind the statement. It also offers additional features such as key phrase extraction, language detection, sentiment analysis, translation, and also identify entities on your own text.

7. Amazon Machine Learning

Amazon's machine learning API can perform a lot of different functions. It has the capacity to perform functions such as fraud detection, content personalization, record classification, and customer churn prediction. Additionally, it allows developers to quickly train and deploy their own versions. But, Amazon's API isn't accessible, but it's available for a pay-as-you-go payment program.

8. BigML

BigML is a Machine studying REST API that allows developers to quickly build and deploy AI models for your programs. This API allows building predictive models that include supervised and unsupervised machine learning jobs, as well as machine learning pipelines. The best part is that BigML allows for creating, retrieving, updating, and deleting BigML tools using standard HTTP methods.

9. Google Cloud APIs

Google has ever been into invention, and also the one place where it really shines is machine learning. Google has an whole suite of Cloud APIs which were made to help simplify a programmer's tasks. Google's machine learning APIs comprise Cloud Vision API, Cloud Speech API, Natural Language API, Translation API, and Dialogflow API.

Cloud Vision API -- comprises picture labeling, detection for face, emblem and landmarks, optical character recognition, and detection of explicit content.

Cloud Speech API -- includes speech recognition, audio conversion from a microphone or a file, conversion to text in over 80 languages.

Natural Language API -- comprises structure analysis, meaning of text, opinion analysis, entity recognition, and text annotations.

Translation API -- Translates from 1 language to another.

Dialogflow API -- A complete development package for conversational interfaces such as chatbots, voice-powered apps, etc..

10. Wi AI

Wit AI is a natural open-source language processing platform that offers the function to incorporate intelligent speech functionality to mobile and web applications. It offers an intelligent voice port for applications such as home automation, attached cars, smart TV, robotics, smart phones, wearables, etc.. The documentation for Wit.ai is clean and easy to comprehend. It includes code samples, SDKs for many popular platforms and languages, fast start guides, along with a complete Wit app manual.

Conclusion

With machine learning here to stay, developers will really have to up their game if they would like to remain in the contest. All these 10 APIs should help you get an advantage over the others. In case you have any preferred APIs, please tell us in the comments section below.