50 Useful Machine Learning & Prediction APIs
We present a list of 50 APIs selected from areas like machine learning, prediction, text analytics & classification, face recognition, language translation etc. Start consuming APIs!
Face and Image Recognition
- Animetrics Face Recognition: This API can be used to detect human faces in pictures and match them against a set of known faces. The API can also add or remove a subject from a searchable gallery, and add or remove a face from a subject.
- Betaface : a facial recognition and detection web service. Features include multiple faces detection, faces cropping, 123 face points detection (22 basic, 101 advanced), faces verification, identification, similarity search in very large databases etc
- Eyedea Recognition: a recognition service that offers eyeface, vehicle, copyright and plate detection. The main value of the API could be to have access to an instant understanding about objects, users, and behaviors.
- Face++: a facial recognition and detection service that provides detection, recognition and analysis for use in applications. Users can make calls to train the program, detect faces, recognize faces, group faces, manipulate people, create face sets, create groups, and get info.
- FaceMark: FaceMark is an API capable of detecting 68 points on a frontal face photograph, and 35 for a profile face photograph.
- Google Cloud Vision API: helps you find your favorite image, and get rich annotations of it quickly and at scale. It classifies images into thousands of categories (e.g., "boat", "lion", "Eiffel Tower"), detects faces with associated emotions, and recognizes printed words in many languages.
- Microsoft Project Oxford Vision: allows developers to access and integrate the vision functionality of Microsoft Project Oxford. Some example API methods include processing images, detecting images, and returning thumbnail images.
- Rekognition: provides facial and scene image recognition optimized for social photo applications. Utilizing the eyes, mouth, face and nose along with mood recognition and sex dependent characteristics the Rekognition API can predict sex, age and emotion.
- FaceRect: an API capable of detecting faces in images. The API can detect multiple faces within a given image, including both frontal and profile faces, and search for face features (eyes, nose, mouth) within each detected face.
- Kairos: a facial recognition API that allows users to integrate advanced security features into their applications and services
- Skybiometry Face Detection and Recognition: provides a face detection and recognition service and can be used as a drop-in replacement for discontinued face.com API.
Text Analysis, NLP, Sentiment Analysis
- AlchemyAPI: AlchemyAPI offers artificial intelligence as a service. Currently available text analysis functions include entity extraction, sentiment analysis, keyword extraction, concept tagging, relation extraction, text categorization, author extraction, language detection, text extraction, microformats parsing and RSS/ATOM feed detection.
- AlchemyAPI Keyword Extraction: extracts topic keywords from text, HTML, or posted web-based content. This API normalizes the targeted text, removing ads, navigation links, and other unnecessary content, then extracts topic keywords.
- Bitext Sentiment Analysis: a suite of multilingual semantic services. Currently four semantic service are available: entity and concept extraction, sentiment analysis and text categorization.
- Calais: Using natural language processing, machine learning and other methods, Calais categorizes and links your document with entities (people, places, organizations, etc.), facts (person "x" works for company "y"), and events (person "z" was appointed chairman of company "y" on date "x").
- Semantic Biomedical Tagger: has a built-in capability to recognize 133 biomedical entity types and semantically link them to the knowledge base systems.
- Free Natural Language Processing Service: sentiment analysis, content extraction, and language detection.
- nlpTools: decodes online news sources for sentiment analysis and textual classification. In order to analyze the sentiment or classify of a line of text, developers may use this API to receive a return of a category label and a conditionality on the piece ranging from positive, neutral, to negative sentiment.
- Diffbot Analyze: provides developers tools that can identify, analyze, and extract the main content and sections from any web page.
- Skyttle: Market Sentinel's text mining engine, which analyses text for topical keywords and phrase-level sentiment. Languages supported are English, French, German, Russian.
- Speech2Topics: analyzes audio and video to extrapolate big data, using natural language processing and speech recognition.
- TweetSentiments: performs semantic analysis of tweets using a Support Vector Machines algorithm. Doing so, it is able to determine whether tweets are positive, negative or neutral in sentiment.
- Text Processing: provides functions that include summarizing documents, tagging documents, stemming words to their base forms, removing stopwords, tagging parts of speech (POS), translating from Bahasa Indonesia to English, and retrieving word definitions.
- MeaningCloud Text Classification: The Text Classification API performs pre-classification tasks like: extracting text, tokenization, stopword removal and lemmatization. Using rule-based filtering and statistical document classification, the API can perform accurate classification across a wide range of environments.
- Google Translate: Currently in second version, google translate provides researchers, in the field of automatic machine translation, tools to help compare and contrast with, and build on top of, Google's statistical machine translation system.
- LangId: a fast way to retrieve information about any sort of language, without specifying the language.
- MotaWord: provides translations in over 70 languages. The API also lets developers get quotes for each translation, submit translation projects along with documents and style guides, track the progress of translation project and get activity feeds in real time.
- WritePath Translation: API allows developers to access and integrate the functionality of WritePath with other applications. Some example API methods include retrieving word counts, posting documents for translations, and retrieving translated documents and text.
- IBM Watson Language Translation: uses statistical machine translation techniques to provide domain-specific translations. They currently offer three domains(conversational, patent & news) that can translate between a total of seven languages.
Did we miss your favorite APIs? We will keep updating the list ! Tell us what's on your mind in the comments.
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