Making cities safer: data collection for Vision Zero
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A critical part of enabling cities to implement their Vision Zero policies – the goal of the current National Transportation … Continue reading
A critical part of enabling cities to implement their Vision Zero policies – the goal of the current National Transportation … Continue reading →
Modern advanced analytics applications make use of machine learning techniques and contain multiple steps of domain-specific and general-purpose processing with … Continue reading →
In conjunction with this week’s AMPLab End of Project event, Ben Lorica of O’Reilly has published a blog post giving … Continue reading →
The November 2016 issue of CACM features an overview paper on Apache Spark written by Spark contributors from AMPLab and … Continue reading →
PDF Parallel processing frameworks (Dean and Ghemawat, 2004) accelerate jobs by breaking them into tasks that execute in parallel. However, … Continue reading →
The Computing Research Association (CRA) is a leading organization for promoting research into Computer Science and related Computing disciplines. CRA’s … Continue reading →
This paper considers two learning from demonstrations algorithms in terms of how they acquire demonstrations. “Human-Centric” (HC) sampling is the … Continue reading →
Analysts often clean dirty data iteratively–cleaning some data, executing the analysis, and then cleaning more data based on the results. … Continue reading →
The ActiveClean project (which recently won a best demo award at SIGMOD 2016) got some press in the blog “Science … Continue reading →
The West Big Data Innovation Hub (WBDIH) is excited to host a Data Hackathons: Lessons Learned and Best Practices Workshop … Continue reading →