Machine Learning Platforms.

A machine-learning platform offers data scientists the building blocks for creating a solution to a data science problem. The platform also provides these experts with an environment where they can incorporate the results into products and business processes. machine-learning platform needs to provide data scientists with all the support they need when carrying out data and analytics process. These process covers visualization, interactive exploration, deployment, performance engineering data preparation, and data access.

1. Apache PredictionIO – Open-source stack that incorporates an open-source application server for machine learning . Apache PredictionIO is a way to build predictive engines that can meet any artificial intelligence process. the platform with the event server have a template gallery.
2. Caffe – Developed by the Berkeley Vision and Learning Center (BVLC) in collaboration with a developer community. Caffe was created to equip developers with an automatic inspection tool that is based on images. Caffe is used by some of the popular brands in the world, including Pinterest and Facebook.
3. Accord.NET Framework – Accord is an Image and audio processing libraries are developed with the C# programming language and then combined with the Accord.NET framework. Within the Accord.NET framework, developers can create a range of apps for commercial use that rely on machine learning, such as computer vision, signal processing, pattern recognition, and machine listening.
4. H2O – H2O presents developers with the tools they require to analyze data sets in the Apache Hadoop file systems as well as those in the cloud. H2O was created for the Python, R, and Java programming languages by H2O.ai. This open-source software makes it easy for developers to apply both predictive analytics and machine learning to a variety of situations.
5. ai-one – With ai-one, developers can produce intelligent assistants that are applicable to nearly any software application. ai-one list of resources comprises of developer APIs, a document library, and building agents that can be used to convert data into rule sets that support ML and AI structures.
6. Torch – Torch includes a scripting language, a scientific computing framework, and an open-source ML library with the Lua programming language as its foundation. Torch supports deep machine learning through a collection of algorithms and has been used by DeepMind and the Facebook AI Research Group.

To get started on machine learning, it is preferable to geo through the list of options and decide based on your dependence on programming language and your solution architecture.