By Chuck Calio Published September 11, 2018
Data scientists surface new and valuable insights from a wide variety of relational, semi-structured and unstructured data sources. This ‘magic’ is accomplished by leveraging the combination of modern accelerated IT infrastructure along with powerful machine learning (ML) and deep learning (DL) algorithms. Data scientists often have advanced academic degrees along with deep skills, ability, and experience spanning multiple programming languages and other supporting tools. Unfortunately, data scientists can struggle to optimize their productivity and reduce their time spent on low value tasks.
Based on our team’s work on hundreds of engagements, we have observed three major inhibitors that reduce data scientists’ productivity and cause unnecessary loss of time and money:
IBM PowerAI was designed from the ground up with the next generation of data scientists in mind. Our goal is to create an enterprise software distribution of the open source machine learning / deep learning frameworks and then add value and support around this core.
Clients and data scientists are choosing our IBM PowerAI offering for four key reasons:
A modern data science platform can provide companies with a competitive advantage. For more information on IBM PowerAI, please visit our Developer’s Portal at https://developer.ibm.com/linuxonpower/deep-learning-powerai/.
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