Artificial intelligence could revolutionize the legal profession.
Machine learning solutions drive exponential progress in today's cloud computing era. The ability to leverage Big Data analytics and spot patterns offers critical competitive advantage.
Google Cloud Machine Learning Engine, which leverages the search giant's ML expertise, is a managed service that allows developers and data scientists to build and deploy machine learning models.
Alteryx offers a unified data science and machine learning platform, Alteryx Analytics, that is designed to aid developers and data scientists in building machine learning models through a streamlined workflow.
The SAP data science framework provides powerful machine learning tools that run within the SAP Cloud Platform. The machine learning functions are designed to work with various SAP products and applications.
RapidMiner offers a unified data science platform with a suite of products that manage data preparation, machine learning and predictive modeling.
Microsoft Azure Machine Learning Studio offers a complete browser-based visual drag-and-drop solution for developing machine learning applications and services.
IBM Watson Studio delivers an integrated environment designed to facilitate development, training, management, and deployment of machine learning, deep learning and AI-powered applications.
SAS offers a robust machine learning platform that supports end-to-end data mining and machine learning within a visual development interface.
AWS SageMaker is a machine learning platform that supports data processing and analytics within Amazon Web Services (AWS).
Are Facebook, Google, and other online giants simply too big and too ubiquitous to suffer the traditional economic penalties for violating public trust? If so, we are on a slippery slope indeed.
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From better "chatbots" for customer service to data analytics watching your company's activities, artificial intelligence (AI) in business is rapidly becoming a commonly-used competitive tool.
Data mining is the means by which organizations extract value from their data, and it has become increasingly central to maintaining a competitive edge in business.
The chipmaker has made some impressive staffing changes and turned in an outstanding financial report.
While the more highly granular microservices has evolved from the earlier SOA, both approaches are still widely used. Where SOA is enterprise-focused, microservices is application-focused.
While DevOps and microservices are separate technologies, they work well together to speed the pace of software development in the cloud computing era.
For organizations seeking container management, the underlying operating system and cloud service provider determines the optimal container management solution.
Red Hat’s OpenShift Container Platform provides an on-premises Platform-as-a-Service (PaaS) approach to container management. It uses Docker containers that are managed by Kubernetes.
Kubernete, developed by Google but now managed by the Cloud Native Computing Foundation, delivers an open source system for managing and orchestrating containers in the cloud.
Working within the Microsoft Hyper-V environment, this container platform uses Docker and Windows PowerShell with a command line interface to configure, deploy and manage containers and microservices.
