O que fazemos

There are demands for good mathematicians to write algorithms that can churn through billions or trillions of data points and show where patterns emerge. The Economist data issue (http://www.economist.com/node/15557443) raised this issue as follows: "During the recent financial crisis it became clear that banks and rating agencies had been relying on models which, although they required a vast amount of information to be fed in, failed to reflect financial risk in the real world. This was the first crisis to be sparked by big data—and there will be more". With proper management, big data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. This meetup is for big data science. Data scientists are welcome to join this group and exchange ideas.

Próximos eventos (5+)

Artificial Intelligence and Big Data Sciences

Microservices World -- Expo Discovery Stage located within Hall 3, San Jose Convention Center

The meetup will take place on the Microservices World -- Expo Discovery Stage located within Hall 3 of the San Jose Convention Center. 2:30 P.M. - 3:00 P.M. Introduction / Networking 3:00 P.M. - 3:50 P.M. Session 1 Title: A Scalable Artificial Intelligence Data Pipeline for Accelerating Time to Insight Speaker: Dr. Sanhita Sarkar, Global Director, Analytics Software Development, Western Digital Abstract: Artificial intelligence (AI) requires processing power and adequate storage while executing various deep learning (DL) frameworks. The training and deployment stages of a DL system have different data and processing needs. On one hand, the large volumes of data during training demands systems with support for massive storage capacity, multiple data formats and protocols for processing dispersed data sets, and sharing of data and models across applications. On the other hand, AI deployment for delivering inference on incoming data requires fast access to the data to meet the demand for AI responsiveness for applications. The processing and storage needs vary for the different phases of an AI data pipeline comprising of data ingestion, model training and model serving. Disaggregation of GPUs, flash and object storage can enable the delivery of rapid response times and scaling requirements of an AI data pipeline, without compromising on data persistence, quality, durability and cost. Speaker Bio: Sanhita Sarkar is a Global Director, Analytics Software Development at Western Digital, where she oversees software design and development of analytical features and solutions from edge to data center/cloud. She focuses on key vertical markets such as the Industrial Internet of Things (IIoT), Defense and Intelligence, Media and Entertainment, and Genomics and Healthcare. Sanhita previously held leadership positions at Teradata, SGI, and Oracle. She received her Ph.D. in Electrical Engineering and Computer Science from the University of Minnesota, Minneapolis. 3:50 P.M. - 4:05 P.M. Q/A

Artificial Intelligence and Big Data Sciences

These meetups are for general big data sciences, machine learning, mathematical models, IoT (Internet of Things) applications, ICT (Information and Communication Technologies) applications, genome re-sequencing on Hadoop clusters and No-sql databases. Industry experts provide hands-on sessions on general machine learning techniques, IoT, ICT, genome analysis along with statistical analysis in graph databases and other no-SQL databases. Students (future data scientists) from High Schools / Colleges / Universities are welcome to join "hands-on sessions" and give "short talks" on IoT, ICT, genomics and topics related to data sciences. One parent is allowed with each high school or college student. Attendees for hands-on sessions should bring laptops with Java6 or Java7 and must have Amazon EC2, Amazon EMR and Amazon S3 accounts.

Artificial Intelligence and Big Data Sciences

These meetups are for general big data sciences, machine learning, mathematical models, IoT (Internet of Things) applications, ICT (Information and Communication Technologies) applications, genome re-sequencing on Hadoop clusters and No-sql databases. Industry experts provide hands-on sessions on general machine learning techniques, IoT, ICT, genome analysis along with statistical analysis in graph databases and other no-SQL databases. Students (future data scientists) from High Schools / Colleges / Universities are welcome to join "hands-on sessions" and give "short talks" on IoT, ICT, genomics and topics related to data sciences. One parent is allowed with each high school or college student. Attendees for hands-on sessions should bring laptops with Java6 or Java7 and must have Amazon EC2, Amazon EMR and Amazon S3 accounts.

Artificial Intelligence and Big Data Sciences

These meetups are for general big data sciences, machine learning, mathematical models, IoT (Internet of Things) applications, ICT (Information and Communication Technologies) applications, genome re-sequencing on Hadoop clusters and No-sql databases. Industry experts provide hands-on sessions on general machine learning techniques, IoT, ICT, genome analysis along with statistical analysis in graph databases and other no-SQL databases. Students (future data scientists) from High Schools / Colleges / Universities are welcome to join "hands-on sessions" and give "short talks" on IoT, ICT, genomics and topics related to data sciences. One parent is allowed with each high school or college student. Attendees for hands-on sessions should bring laptops with Java6 or Java7 and must have Amazon EC2, Amazon EMR and Amazon S3 accounts.

Eventos realizados (118)

Artificial Intelligence and Big Data Sciences

Fremont Main Library, Fukaya Room B

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