Artificial Intelligence, a rapidly-developing technology, has numerous applications in many fields. AI is used by many organizations to improve their predictive modeling, fraud and risk analysis, customer intelligence, and advertising technology.
However, machine learning technology should only be used with caution. Prior to deploying machine learning models, it is important that companies ensure quality assurance of the data collected.
5. Wit.ai
Wit, a natural language interface designed for applications, can transform sentences into structured information. Its API supports HTTP GET calls to return the extracted meaning of a sentence, based on example sentences.Wit has a large library of entities that it can recognize. These entities can include numbers and dates as well as text that is free, such words or phrases.
They are particularly useful for extracting the raw character strings of an expression. This makes them great for creating message board posts, agenda entries, or other interactive tasks. To be correctly recognized, they need more examples than any other entity.
You can set up multiple intents, and provide relevant expressions for testing them against. You can do this by clicking on the Intents screen, and you'll see the results.
4. Animetrics Face Recognition
Animetrics Face Recognition API makes it possible to recognize and identify human faces from a photo. It can also determine the orientation on three axes.This API is useful for facial features, landmarks, age/gender recognition, and other purposes. This API can also correct off-angle images.
Animetrics' Face Recognition features SetPose, which allows you to set the desired pose for your facial photos if they were taken at an unusual angle.
Other features include gender classification and positioning of specific features.
There are many options available. Prices vary depending on the included features. The basic plan costs nothing, and the paid plans start at 49 USD per calendar month and go up to 999 US dollars each month.
Face RecognitionTM is a tool to assist users in recognizing and analyzing faces, comparing them, and creating new ones. It recognizes 22+101 facial landmarks, as well as 40+ facial attributes such as gender expression and age content. All this with ease.
3. Alexa Skill Management API
Developers can manage and customize the skills displayed within Amazon Alexa by using the Alexa Skill ManagementAP. It allows developers to monitor skill usage within Amazon's developer console. They can also send data via Alexa event to other places to further analyze the data.The API supports a range of use cases, such as smart home, flash briefing, education and business/productivity. Standard language processing models reduce the need for developers build voice interaction models, and also lower development costs.
Additionally, the API comes with a Python SDK. This makes it much easier to develop your back-end cloud service. This reduces the code required to process Alexa responses and requests, as well other common skill tasks.
These features are not the only ones available. The Alexa Routines Kit allows skill developers to show customers prebuilt routines whenever they interact with their skill. Developers can embed shopping capabilities in their skills using the Alexa Shopping Kit. Customers will be able to shop without leaving the skill.
2. BigML
BigML, an AI platform, gives developers all the necessary tools to build intelligent applications. It allows them to create customized experiences with powerful voice processing and accurate predictions.BigML is a powerful, flexible infrastructure that allows users to create both unsupervised and supervised models. It has nine pre-built datasets, as well as the ability to upload your own data.
A table-like preview lets users view quickly the results of formulas. Formula autocompletion is a great feature that allows coders to work faster.
BigML algorithms provide superior performance and the ability to scale to meet organizational needs. This allows data scientists, model developers, and analysts to spend their time on more important analytics tasks than managing infrastructure management.
BigML is a command-line tool that automates processes. Users need only write one-line code to modify task modes immediately.
1. Google Assistant API
Google Assistant is a voice activated digital assistant that uses AI technologies for contextual information and user actions. It is the core of Google's AI first strategy and will be a major influence on how people interact with other Google products.Small businesses, for instance, can outsource tasks that were previously done by a human worker to save money. You can also use it to improve employee efficiency and productivity by streamlining workflows.
Developers have the ability to use Google Assistant API to build voice-activated apps that enable users to control their devices and make purchases. Developers can also launch Android apps using voice commands that match predefined semantic pattern or built-in intents.