Machine learning is the science of getting computers to act without being explicitly programmed. The new R2D3 Blog offers an instructive Visual Introduction to Machine Learning.
In this video from the Barcelona Supercomputer Center, Big Data is presented as a key challenge for researchers studying global climate change. “Changes in the composition of the atmosphere can affect the habitability of the planet by modifying the air quality and altering long-term climate. Research in this area is devoted to the development, implementation and refinement of global and regional state-of-the-art models for short-term air quality forecasting and long-term climate predictions.”
Early Bird registration rates are now available for ISC Cloud & Big Data Conference, which takes place Sept. 28-30 in Frankfurt, Germany. This year the event will kick off with one full day of workshops. The new program will highlight performance demanding cloud and big data applications and technologies and will consist of three tracks: Business, Technology and Research.
Over at NERSC, Linda Vu writes that the SciDB open source database system is a powerful tool for helping scientists wrangle Big Data. “SciDB is an open source database system designed to store and analyze extremely large array-structured data—like pictures from light sources and telescopes, time-series data collected from sensors, spectral data produced by spectrometers and spectrographs, and graph-like structures that illustrate relationships between entities.”
Today Intel Corporation and BlueData announced a broad strategic technology and business collaboration, as well as an additional equity investment in BlueData from Intel Capital. BlueData is a Silicon Valley startup that makes it easier for companies to install Big Data infrastructure, such as Apache Hadoop and Spark, in their own data centers or in the cloud.
“CDSW’s organizers are professional programmers and data scientists and several of us have experience teaching data science in more traditional university and corporate settings. Our talk will describe how “democratized” data science is similar to — and sometimes extremely different from — these more traditional approaches. We will talk about some of the challenges we have faced and highlight some of our most inspirational successes.”
“Despite the growing abundance of powerful tools, building and deploying machine-learning frameworks into production continues to be major challenge, in both science and industry. I’ll present some particular pain points and cautions for practitioners as well as recent work addressing some of the nagging issues. I advocate for a systems view, which, when expanded beyond the algorithms and codes to the organizational ecosystem, places some interesting constraints on the teams tasked with development and stewardship of ML products.”
In this video from IDF 2015, Intel and Oregon Health & Science University (OHSU) announce the Collaborative Cancer Cloud, a precision medicine analytics platform that allows hospitals and research institutions to securely share patient genomic, imaging, and clinical data for potentially lifesaving discoveries.
The big memory “Blacklight” system at the Pittsburgh Supercomputer Center will be retired on Aug 15 to make way for the new “Bridges” supercomputer. “Built by HP, Bridges will feature multiple nodes with as much as 12 terabytes each of shared memory, equivalent to unifying the RAM in 1,536 high-end notebook computers. This will enable it to handle the largest memory-intensive problems in important research areas such as genome sequence assembly, machine learning and cybersecurity.”