After almost two decades of software development, term – DevOps was coined and officially given importance to collaboration between development and deployment of software systems. In this early stage of Data Science field, use of standardized and empirical practises like DevOps will definitely speed up its evolution.
SnappyData is launching a FREE cloud service called iSight-Cloud so anyone can try our engine and provide us some feedback. You can try our simple demos in a visual environment or even bring your own data sets to try.
Now in open beta, IBM Data Science Experience (DSX) delivers Machine Learning, Collaboration, and Creative capabilities in an open and integrated environment for team data science, including many productivity features for next-generation data science,
Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis.
What you don't know can hurt you, especially in predictive modeling. Read great examples how exploring your data before creating models will help you spot problems before your build incorrect models.
The keys to self-service analytics success are organizational. In addition to a governed self-service architecture, companies need to establish governance committees and gateways, create federated organizations with co-located BI developers, and provide continuous education, training, and support. Learn how to do this in this report.
Visit SAP resource center to learn how to accelerate decisions with automated predictive techniques and results, deploy and manage thousands of predictive data sets and test-drive a fully functional copy of SAP BusinessObjects Predictive Analytics software.
Businesses are producing a greater number of intelligent applications; which traditional databases are unable to support. A new class of databases, Hybrid Transactional and Analytical Processing (HTAP) databases, offers a variety of capabilities with specific strengths and weaknesses to consider. This article aims to give application developers and data scientists a better understanding of the HTAP database ecosystem so they can make the right choice for their intelligent application.
Top 20 Python Machine Learning Open Source Projects, updated
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