New tutorials and articles Using data science to manage a software project in a GitHub organization In part 1 of this article series, you'll create a basic data science skeleton. In part 2, you'll explore your project with Jupyter Notebook and deploy it to the Python Package Index. 5 tips for machine learning success outside of Silicon Valley IBM Architect Jean-François Puget offers five concrete suggestions for getting the most from machine learning for those outside of the Valley. Tracking cryptocurrency with serverless functions Monitor your Bitcoin hoard with IBM Cloud Functions writing data to Cloudant. Analytics powered by Machine Learning Watson Explorer Community Edition helps you be the data science hero at your company by uncovering and anticipating the underlying reasons for costly, reputation-crippling issues. If you can figure this out, maybe you can prevent these issues. 3 must have capabilities to unify data governance Part 1 answers the question "can data governance create user satisfaction?" Part 2 focuses on user empowerment, data sharing, and MDM technology support. Leverage data against other data sources Want to know what markets to target for increased sales? Learn how to link external and public data to your existing data to gain insights for your sales team. Popular videos
Create a DeepLearning anomaly detector using SystemML Data Science Experience: Run Shiny applications in RStudio. Events IBM Cloud Private and WebSphere Application Server: A single platform to harness the power of private cloud˘ 6 December 2017 at 10:30 EST Make the most with Watson Discovery: A technical introduction˘ 6 December 2017 at 1:00 EST Bridge the gap between data scientists and business users ˘ 13 December 2017 at 11:00 EST
Big Data and Analytics Summit Canada 2018˘ 3-14 February 2018 Toronto, ON Index - San Francisco 2018˘ 20-22 February, 2018 San Francisco, CA |
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