Gradient Flow

Tag: data science

  • Semi-automatic method for grading a million homework assignments

    [A version of this post appears on the O’Reilly Strata blog.] One of the hardest things about teaching a large class is grading exams and homework assignments. In my teaching days a “large class” was only…

  • Data Analysis: Just one component of the Data Science workflow

    [A version of this post appears on the O’Reilly Strata blog.] Judging from articles in the popular press the term data scientist has increasingly come to refer to someone who specializes in data analysis (statistics, machine-learning,…

  • Data analysis tools target non-experts

    [A version of this post appears on the O’Reilly Strata blog.] A new set of tools make it easier to do a variety of data analysis tasks. Some require no programming, while other tools make it…

  • Tightly integrated engines streamline Big Data analysis

    [A version of this post appears on the O’Reilly Strata blog.] The choice of tools for data science includes1 factors like scalability, performance, and convenience. A while back I noted that data scientists tended to fall…

  • Data scientists tackle the analytic lifecycle

    [A version of this post appears on the O’Reilly Strata blog.] What happens after data scientists build analytic models? Model deployment, monitoring, and maintenance are topics that haven’t received as much attention in the past, but…

  • HBase looks more appealing to data scientists

    [A version of this post appears on the O’Reilly Strata blog.] When Hadoop users need to develop apps that are “latency sensitive”, many of them turn to HBase1. Its tight integration with Hadoop makes it a…

  • It’s getting easier to build Big Data Applications

    [A version of this post appears on the O’Reilly Strata blog.] Hadoop’s low-cost, scale-out architecture has made it a new platform for data storage. With a storage system in place, the Hadoop community is slowly building…

  • How signals, geometry, and topology are influencing data science

    [A version of this post appears on the O’Reilly Strata blog.] I’ve been noticing unlikely areas of mathematics pop-up in data analysis. While signal processing is a natural fit, topology, differential and algebraic geometry aren’t exactly…

  • Tachyon: An open source, distributed, fault-tolerant, in-memory file system

    [A version of this post appears on the O’Reilly Strata blog.] In earlier posts I’ve written about how Spark and Shark run much faster than Hadoop and Hive by1 caching data sets in-memory. But suppose one…

  • Simpler workflow tools enable the rapid deployment of models

    [A version os this post appears on the O’Reilly Strata blog.] Data science often depends on data pipelines, that involve acquiring, transforming, and loading data. (If you’re fortunate most of the data you need is already…