In this post, I have collected 20 best API built on ML ( machine learning ) and prediction. They are divided in 4 groups by the area of implementation:
- Image and facial recognition
- Machine learning and predictibility;
- NLP, text analysis, and sentiment analysis;
- Language translation.
Image and facial recognition
Though the API has been released less than a year ago, it has firmly established itself as a leader amongst similar offerings.
One of the perks of the API is that it can tell a difference between a real face and a picture of it thanks to spoof detection. Also, TrueFace offers reusable snippets of code.
You can use Kairos both to recognise a human face and to analyze the one on the picture. The API has a pretty big set of features, such as:
- gender and age detection;
- attention measurement;
- emotion detection;
- ethnicity detection;
- finding a facial match (good news for security apps).
3. Amazon Rekognition
The API is a good fit for developers who create apps and software that’s integrated into Amazon Web Service. With Amazon Rekognition, here’s what you can do:
- Analyze images to find out whether they have suspicious content;
- Detect and select the text in images;
- Compare two faces (that means, you can understand whether it’s the same person’s face on two different photos);
- Scan emotions.
4. Face Recognition and Face Detection
The API is developed by Lambda Labs. When a user puts in the URL of an image, the API is able to tell whether or not there’s a celebrity on the photo and who exactly is pictured, like this:
Exept for this feature, there are a few others:
- after sending a picture URL for analysis, a user will find out whether the photo contains faces, how many of them are there. The API will also pinpoint the main facial features (nose, mouth, eyes).
The API is among the cheapest on the market, so if you are new to facial recongition and unsure of whether you really need the feature in the app, it’s a good starting point.
5. Eyedea Recognition
This API can come in handy for someone who wants to collect insights about consumers behaviors, emotions, etc. The API not only analyzes faces but also pays attention to context — where is the person on the picture located, what objects are nearby — all this data provides a deeper understanding of a potential client, prospect, etc.
Good news is, FaceRect is a completely free API for facial recognition. Still, its features are quite powerful:
- defines multiple faces on the photo;
- the API detects the facial features of every face on the picture;
- JSON output is produced for every face as well.
7. IBM Watson Visual Recognition
IBM is quite famous for implementing innovation and technological advancements in its solutions. So, no wonder that when a company of a scale this global produces a facial recognition API, it’ll turn out to be extremely well-done.
Here are the main features of the API:
- understands the contents of images;
- determines the age and gender of people on photos;
- finds similar images to the one previously analyzed;
- the API can be trained by the user who can create custom concepts.
8. Skybiometry Face Detection and Recognition
The face detection by Skybiometry is also a solid solution that allows the detection of people with or without glasses, captures multiple faces on the photo and analyses their emotion.
Also, the API gets updated quite frequently, so new features may appear pretty soon.
9. Antimetrics Face Recognition
In order to analyze and recognise faces more efficiently, the API works by transforming a 2D picture into a 3D model. The recognition is performed by detecting a face and comparing it to an existing set of faces until the match is found.
10. Face ++
The API can be used for web. It also has an offline SDK for iOS and Android. It can provide facial detection and comparing even when a user’s phone has no reception. That gives a broader range of possibilities to developers.
Machine Learning and predictibility
11. Google Cloud Prediction API
Speaking of predictibility APIs, it would be, at the very least, weird to not mention the one developed by Google. Google Cloud Prediction API can predict new trends based on the old ones. Here’s what you can use it for:
- predict what movie a user wants to watch next;
- based on email opening habits, the API can classify whether an email is needed or spam;
- studying one’s shopping habits, the API can predict how much money will a user spend per day.
12. Big ML
Big ML is an API that allows you to operate datasets, clusters, predictions, models, batches comfortably. It’s an easy-to-use machine learning service that can be integrated to your app or software in a few clicks.
With this API, you can create a recommendation engine for a shopping website or software. In a few clicks, a user can increase conversion by offering the products that will be complementary to those a user has already bought.
The API provides the environment for development, prototyping, and deploying of data patterns. A user can deploy the models both localy and in the cloud. MLJAR offers a unified interface for different project and the built-in hyper-parameter search.
Bitext is the API that allows a user to get more insights and useful data from social media mentions, website ratings, etc. Here are the technical highlights of the API:
- JSON output;
- Asynchronous calls;
- HTTPS security.
Also, good news is, the API is free.
Swift API uses machine learning and data processing to deliver insights to retailers based on in-store transactions and online behavior of customers. Thanks to data processing, the app can predict:
- supply chain;
- shopper marketing;
- delivery decisions.
The API offers a machine learning environment with 14 classifiers and NLP-empowerment. Its features include:
- sentiment analysis;
- readability assessment;
- topic classification;
- language recognition;
- spam detection.
InsideView is a Machine Learning-powered API that helps SMEs fasten sales and marketing. It aggregates user data from thousands of different sources and turn it into a consumable form.
It helps sales-managers identify the decision-maker within the company and find the right lead.
Language translation and recognition
19. Google Cloud Speech-to-Text
The API allows a user to turn the audio of different length to text. The dataset has over 120 languages which broadens the range of possibilities for developers.
The API has proper formatting and recognises proper nouns. Also, there are pre-built models for specific case of use.
The API’s main positioning is “bringinig artificial intelligence everywhere”. The solution is intelligent and powerful indeed. Here are only some of its features:
- deep meaning understanding (being able to identify multiple questions from one sentence);
- attention to context (the location of the user or his previous contacts with the system);
- the API identifies music and audio.
Are there any other things you’d like me to cover? If so, go on with suggestions.
That is a wrap. Thanks for stopping by.
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You can also check out our post on: Unsupervised learning with Python