A critical part of enabling cities to implement their Vision Zero policies – the goal of the current National Transportation Data Challenge – is to be able to generate open, multi-modal travel experience data. While existing datasets use po…
This gallery contains 6 photos. A critical part of enabling cities to implement their Vision Zero policies – the goal of the current National Transportation … Continue reading → The West Big Data Innovation Hub (WBDIH) is excited to host a
The West Big Data Innovation Hub (WBDIH) is excited to host a Data Hackathons: Lessons Learned and Best Practices Workshop on September 15 as part of the historic first International Data Week in Denver. One of four hubs recently launched w…
This is a guest blog post originally published on the Databricks blog. For the past few months, we have been busy working on the next major release of the big data open source software we love: Apache Spark 2.0. Since Spark 1.0 came out two…
I am very pleased to announce that Julian Shun has been awarded the ACM’s doctoral dissertation award for his 2015 CMU doctoral thesis “Shared-Memory Parallelism Can Be Simple, Fast, and Scalable” which also won that year’s CMU SCS distingu…
West Big Data Innovation Hub (WBDIH) All Hands Meeting International House, University of California, Berkeley Now, also available via live stream: http://westbigdatahub.org/live-stream Participants gathering at UC Berkeley for the meeting
Hoping to start a new tradition, I’m giving a Last Lecture on Friday May 6, 2016 at 4PM, which is shortly before I retire. (The premise of these is that if this were the last public lecture you would give, what would you say.) My title is “…
Many of the projects in the AMPLab drive systems for large-scale data analysis to ever-increasing sophistication, speed, and scale. No matter how efficient the algorithm or how powerful the system that runs it, however, the human analyst re…
A major challenge in many large-scale machine learning tasks is to solve an optimization objective involving data that is distributed across multiple machines. In this setting, optimization methods that work well on single machines must be
I’m turning 68 today; 4 of my 6 Ph.D. students are graduating; and the start of the 5-year successor to the AMP and ASPIRE Labs is imminent. Thus, I’ve decided that the time is right to retire from UC Berkeley to allow a recent PhD with a f…
Web applications and services today collect, store and analyze an immense amount of data. As data sizes continue to grow, the bottlenecks in systems for big data analytics have undergone a fundamental change. In particular, with memory band…
KeystoneML is a research project exploring techniques to simplify the construction of large scale, end-to-end, machine learning pipelines. KeystoneML is designed around the principles of composability and modularity, and presents a rich set…