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Slidecast: Announcing the Nvidia Deep Learning SDK

In this slidecast, Marc Hamilton from Nvidia describes the latest updates to the company’s Deep Learning Platform. “Great hardware needs great software. To help data scientists and developers make the most of the vast opportunities in deep learning, we’re announcing today at the International Supercomputing show, ISC16, a trio of new capabilities for our deep learning software platform. The three — NVIDIA DIGITS 4, CUDA Deep Neural Network Library (cuDNN) 5.1 and the new GPU Inference Engine (GIE) — are powerful tools that make it even easier to create solutions on our platform.”

Large-Scale Deep Learning with TensorFlow

We bring you the keynote presentation below from the recent Spark Summit 2016 held in San Francisco on June 6-8. Speaker Jeff Dean joined Google in 1999 and is currently a Google Senior Fellow.

Natero Brings Machine Learning to SaaS Customer Success

Natero aims to empower Customer Success, Sales, and Marketing teams to become data-driven, without having to be data experts. It automatically aggregates and mines all sources of customer data to uncover actionable insights.

Bridging the Gap Between Data Science and Data Engineering

In the compelling keynote address below, Josh Wills, Director of Data Engineering at Slack, discusses an all-too-common theme these days: “Data Engineering and Data Science: Bridging the Gap.”

NVIDIA Supercharges Deep Learning Innovation with Program to Support AI Startups

NVIDIA unveiled a comprehensive global program to support the innovation and growth of startups that are driving new breakthroughs in artificial intelligence and data science. The NVIDIA Inception Program provides unique tools, resources and opportunities to the waves of entrepreneurs starting new companies, so they can develop products and services with a first-mover advantage.

The Future of Data Science

Here at insideBIGDATA, we’re very serious about data science and machine learning. Data science holds the potential to dramatically impact our lives and how we work. Despite its promise, many questions about data science remain.

Syncsort’s Latest Innovations Simplify Integration of Streaming Data in Spark, Kafka and Hadoop for Real-Time Analytics

Syncsort, a global leader in Big Data software, announced new capabilities, including native integration with Apache Spark and Apache Kafka, allowing organizations to access and integrate enterprise-wide data with streams from real-time sources.

Data Science 101: GPU Programming for Beginners

The presentation below is an educational resource that sets the stage for parallel programming with GPUs (graphics processing units) and was sponsored by the Center for Astrophysics and Supercomputing at Swinburne University of Technology. GPUs are becoming quite popular for the implementation of deep learning solutions.

Dell Further Democratizes Advanced Analytics With Latest Release of Statistica

Dell announced a major new release of its award-winning Statistica advanced analytics platform, Dell Statistica version 13.1. This latest version delivers a host of capabilities designed to empower citizen data scientists, help organizations better address growing IoT analytics requirements, and better leverage increasingly heterogeneous data environments.

Data Science 101: Clustering Approaches & Techniques

The presentation below by Derek Kane provides an overview of clustering techniques, including K-Means, Hierarchical Clustering, and Gaussian Mixed Models.