In this Digital age, every organization is trying to apply machine learning and artificial intelligence to their internal and external data to get actionable insights which will help them to be closer to today’s customer.
A few years back it was a field only for data scientists and statisticians, who used to analyze the data, apply data techniques and provide results.
Today many organizations are using APIs to access ready-made algorithms available in the market as they make it easy to develop predictive applications.In fact, you don’t even need to have an in-depth knowledge of coding or computer science to introduce them to your apps.
APIs provide abstraction layers for developers to integrate machine learning into real-world applications without worrying about which technique to use or how to scale the algorithm to their infrastructure.
These APIs can be categorized broadly into 5 groups:
Image and Face Recognition: It understands the content of the image, classifies the image into various categories, detects individual objects and faces, detects labels and logos from the images.
Language Translation: Translate text between thousands of languages, allows you to identify the language the text that you need to analyze was written. Some APIs allow organizations to communicate with the customer in their language.
Speech Recognition and Conversion: Today alot of customer service is handled by Chatbots with underlying APIs helping simple question and answer. Speech to text APIs are used to convert call center voice calls into text for further analysis.
Text /Sentiment Analytics using NLP: With the rise of Social Media, consumers easily express and share their opinions about companies, products, services, events etc. Companies are interested in monitoring what people say about their brands in order to get feedback or enhance their marketing efforts. These APIs can identify, analyze, and extract the main content and sections from any web page. They further help to analyze unstructured text for sentiment analysis, key phrase extraction, language detection and topic detection. There are some tools that also help in spam detection.
Prediction: These APIs, as the name suggests, help to predict and find patterns in the data. Typical examples are Fraud detection, customer churn, predictive maintenance, recommender systems and forecasting etc.
With growing number of free/reasonably priced APIs and a tsunami of data generated every day, the race is on as to which is the best Machine Learning API.
These machine learning APIs are not yet perfect or matured and they will take some time to learn and perform accurately. But they allow faster time to market-based on ready availability, rather than asking data scientist to code the algorithms.
In future, machine learning will lead to revolutions that will intensify human capabilities, assist people in making good choices and help to navigate through the world in powerful ways, like Iron Man's Jarvis.