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    Seeking Reproducibility within Social Science: Search and Discovery

    Julia Lane, NYU Professor, Economist and cofounder of the Coleridge Initiative, presented “Where’s the Data: A New Approach to Social Science Search & Discovery” at Rev. Lane...

    MNIST Expanded: 50,000 New Samples Added

    This post provides a distilled overview regarding the rediscovery of 50,000 samples within the MNIST dataset.  MNIST: The Potential Danger of...

    Learn from the Reproducibility Crisis in Science

    Key highlights from Clare Gollnick’s talk, “The limits of inference: what data scientists can learn from the reproducibility crisis in science”, are...

    Data Scientist? Programmer? Are They Mutually Exclusive?

    This Domino Data Science Field Note blog post provides highlights of Hadley Wickham’s ACM Chicago talk, “You Can’t Do Data Science in a GUI”. In his...

    Managing Data Science as a Capability

    Nick Elprin, CEO at Domino, presented a 3-hour training workshop, “Managing Data Science in the Enterprise”, that provided practical insights and...

    Reproducible Machine Learning with Jupyter and Quilt

    In this guest blog post, Aneesh Karve, Co-founder and CTO of Quilt, demonstrates how Quilt works in conjunction with Domino's Reproducibility Engine...

    Reproducible Dashboards and Other Great Things to do with Jupyter

    Mac Rogers, Research Engineer at Domino, presented best practices for creating Jupyter dashboards at a recent Domino Data Science Pop-Up. Session...

    Git Integration in Domino

    We recently released new functionality that provides first-class integration between Domino and git. This post describes the new feature, and...

    Principles of Collaboration in Data Science

    Data science is no longer a specialization of a single person or small group. It is now a key source of competitive advantage, and as a result, the...

    Achieving Reproducibility with Conda and Domino Environments

    Managing “environments” (i.e., the set of packages, configuration, etc.) is a critical capability of any Data Science Platform. Not only does...

    Domino raises $10.5M in funding for collaborative, reproducible data science

    Today we’re announcing that we have raised $10.5 million in a funding round led by Sequoia Capital. For us, fundraising is simply a means to an end:...

    Reproducible Research in Computational Sciences

    This guest post was written by Arnu Pretorius, a Masters student in Mathematical Statistics at the MIH Media Lab, Stellenbosch University. Arnu's...

    Providing Digital Provenance: from Modeling through Production

    At last week's useR! R User conference, I spoke on digital provenance, the importance of reproducible research, and how Domino has solved many of the...