In this Intel on AI podcast episode: Creating, maintaining and deploying data models that allow businesses to gain actionable insights can require a lot of time and effort due to the vast amount of data to process. Also, machine learning optimization is a resource-intensive process and can be a challenge to accomplish in an industry where achieving fantastic results at speed is the final goal. Carlos Pazos, Product Marketing Manager at SparkCognition, joins the Intel on AI Podcast to show how the SparkCognition Darwin platform is transforming the way that data models are built in the enterprise world. He explains that automated machine learning (AutoML) enables even non-technical users to make use of science and drives organizations to scale the operationalization of ML models. The SparkCognition Darwin platform uses neuroevolution to custom build model architectures creating models in less time than traditional methods and enabling the rapid prototyping of scenarios and insights. Carlos also discusses how using Intel tools like the Intel Message Parsing Interface (Intel MPI) has allowed SparkCognition to provide greater performance to their end users. Also, how the Intel AI Builders program has provided an immense amount of development and marketing guidance to SparkCognition.

To learn more, visit:
sparkcognition.com

Visit Intel AI Builders at:
builders.intel.com/ai

Tags: Accelerating Data Science, AI, artificial intelligence, Automated AI, AutoML, Carlos Pazos, deep learning, Intel MPI, machine learning, natural language processing, neuroevolution, SparkCognition, Supercomputing
 
Posted in: Artificial Intelligence, Audio Podcast, Intel, Intel on AI