Guest Post: 3 Generations of Machine Learning Models – A New Focus on Business Value
Learn about how machine learning works with Minitab software, and how we are entering a third generation of machine learning capabilities you can tap into.
Using Predictive Analytics to Help Seniors Maintain Their Independence
Predictive analytics is helping to advance assessments healthcare workers use to observe the elderly, and potentially detect and treat conditions earlier.
7 Top Talks from the Minitab Insights Conference
See what goes into a great Minitab Insights Conference presentation. Great stories others want to hear. Discovering new tools in Minitab software. Engaging walkthroughs of finding insights in your data, and recommendations on how to act on them. All packed into a few days of learning and fun.
Taking Machine Learning from Myths to Business Reality
You now see “Machine Learning” appearing along with “Big Data”, “AI” or “Internet of Things” as part of the digital transformation of business. Yet this new hype is creating a series of myths, which can obscure the role of data-driven professionals in this transformation. Watch our webinar today.
Industry Expert Greg Kinsey: Black Belts Can (and Should) Drive the Digital Transformation of Manufacturing
Greg Kinsey, Industry Expert, shares his view on the Future of Operational Excellence and the new role of Lean Six Sigma – and how you can be part of it.
The Future of Operational Excellence according to Industry Expert Greg Kinsey
Greg Kinsey, Industry Expert, shares his view on the Future of Operational Excellence and the new role of Lean Six Sigma – and how you can be part of it.
Guest Post: Location Matters – Data Mining Research to Enhance Accuracy, Benefit Future Studies
Research institutions and museums seek to provide the most accurate data possible to record the past and choose where to explore in the future. Modeling the accuracy of data is essential and nailing down geographical locations of specimen samples as exactly as possible is vital to do it effectively.
Guest Post: It’s Tough to Make Predictions, Especially about the Future (even with Machine Learning)
At its core, all Machine Learning algorithms follow a two-part process. First a sequence of increasingly complex functions is fit to part of the data (training data set). Then each model in the sequence is evaluated on how well it performs on the data that was held out (the holdout set).