Gradient Flow

Tag: analytic lifecycle

  • Building and deploying large-scale machine learning pipelines

    [A version of this post appears on the O’Reilly Radar blog.] There are many algorithms with implementations that scale to large data sets (this list includes matrix factorization, SVM, logistic regression, LASSO, and many others). In…

  • Instrumenting collaboration tools used in data projects

    Built-in audit trails can be useful for reproducing and debugging complex data analysis projects [A version of this post appears on the O’Reilly Data blog.] As I noted in a previous post, model building is just…

  • Gaining access to the best machine-learning methods

    [A version of this post appears on the O’Reilly Strata blog and Forbes.] For companies in the early stages of grappling with big data, the analytic lifecycle (model building, deployment, maintenance) can be daunting. In earlier…

  • 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,…

  • Running batch and long-running, highly available service jobs on the same cluster

    [A version of this post appears on the O’Reilly Strata blog.] As organizations increasingly rely on large computing clusters, tools for leveraging and efficiently managing compute resources become critical. Specifically, tools that allow multiple services and…

  • 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…