An API is a set of routines, protocols and tools for building software applications. For KDnuggets' third edition of this post, we removed discontinued APIs from the list of 2017, and updated it with new elements. Within each group of applications, the list is in alphabetical order. API overview is based on information as it has appeared on its URL as of 16-April-2018. Check out where these APIs are put into use!

As the Artificial intelligence & Machine learning based applications evolve, we see numerous mash ups of application program interfaces (APIs) to experiment with. API is a set of routines, protocols, and tools for building software applications. In this post, we removed from the list of 2015 discontinued APIs. We also added new APIs that recently come from giant providers such as IBM, Google, and Microsoft. Within each group of applications, we list in alphabetical order.

As the Artificial intelligence & Machine learning based applications evolve, we see numerous mash ups of application program interfaces (APIs) to experiment with. API is a set of routines, protocols, and tools for building software applications. In this post, we removed from the list of 2015 discontinued APIs. We also added new APIs that recently come from giant providers such as IBM, Google, and Microsoft. Within each group of applications, we list in alphabetical order.

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Use in transforming unstructured data into structured especially in social media monitoring, business intelligence, content recommendations, financial trading and targeted advertising. A live mashup that consumes Alina demonstrates the API's ability to use genetic algorithms and artificial neural networks to analyze historical Bitcoin price fluctuations to predict and automate future trading. Amazon Machine Learning: To find patterns in data. Example uses of this API are applications for fraud detection, forecasting demand, targeted marketing, and click prediction BigML: BigML is a service for cloud-hosted machine learning and data analysis. Users can set up a data source, create a dataset, create a model from the dataset, and then make predictions based on the data.

As the Artificial intelligence & Machine learning based applications evolve, we see numerous mash ups of APIs to experiment with. Get started with this list of selected APIs to explore their capabilities & features in machine learning, prediction, face recognition, image processing, speech recognition etc. Check out where these APIs are put into use!