When should I use machine learning?
With the advent of Industry 4.0 and the industrial internet of things (IIoT), information comes streaming in from many sources. Being able to collect, collate and analyze this information is becoming ever-more critical as companies use this to find insight and improve efficiency and effectiveness. You may already run some data analysis and may ask you the question "When should I use machine learning?”
Learning to Love Correlograms in the Latest Minitab Release
Learn why correlograms, among the new visualizations as part of the recent Minitab release, are such popular and useful tools for advanced analytics.
Feature Engineering for Machine Learning and Predictive Analytics
Explore the importance of feature engineering for machine learning, how it relates to data manipulation and learn proper technique application in Minitab.
What Are the 3 Biggest Challenges to Creating and Sustaining a Culture of Continuous Improvement and Operational Excellence?
Check out our infographic and learn the top three challenges operational excellence and continuous improvement initiatives face at organizations.
Automotive Industry Guidelines: Apply the AIAG-VDA FMEA Methods with Confidence
Learn about the latest automotive industry risk analysis guidelines from the AIAG-VDA and how to align with their FMEA methodology using our forms.
A Food Manufacturer's Secret Process Improvement Recipe for Saving $35 Million
Learn how Master Black Belt Brian Mapani of PremierFMCG saved $35M with a Lean Six Sigma program, Companion and Minitab Statistical Software.
An Innovation Management Case Study from the Minitab Organization
When the Minitab sought innovative ways to leverage Minitab Engage tools, it turned to employees for ideas that ultimately led to a new product offering.
Enhancing and Digitizing the Customer Experience in Financial Services
Explore two examples about automation and harnessing data analysis to enhance and digitize your customers' experience in the financial services sector.