- SAS® Visual Data Science Decisioning powered by SAS® Viya®: Free Trial - Jun 8, 2021.
SAS® Visual Data Science Decisioning provides the ultimate analytics experience. Start your free trial and get access to the latest in data visualization, machine learning, forecasting, model deployment and more.
- Sudoku Rules: Using a Decision Engine to Solve Candidate Pairs - Mar 30, 2021.
Follow along with the author's most recent installment in their quest to solve Sudoku puzzles, this time with the help of a decision engine to solve candidate pairs.
- Sudoku Rules: Using A Decision Engine To Solve Sudoku - Mar 15, 2021.
See the progress the author has made since last time, after setting themselves the challenge of solving Sudoku puzzles using an optimized inference engine, along with a few other advanced features of FICO® Blaze Advisor®.
- Machine Learning in Action: Going Beyond Decision Support Data Science - Nov 20, 2018.
In order to disrupt business, machine learning models must adopt a product-focused approach, which is a much more significant undertaking.
- Are physicians worried about computers machine learning their jobs? - Aug 30, 2017.
We review JAMA article on “Unintended Consequences of Machine Learning in Medicine” and argue that a number of alarming opinions in this pieces are not supported by evidence.
- Streamlining Analytic Deployment: Inside the FICO Decision Management Suite 2.0 - Jul 8, 2016.
This post explains what’s new in the 2.0 version of the FICO Decision Management Suite, and how it can be used by data scientists and others to create stronger customer relationships and provide strategic competitive advantage.
- Interview: Kavita Ganesan, FindiLike on Building Decision Support Systems based on User Opinions - Jul 27, 2014.
We discuss the founding story of FindiLike, Opinion-driven Decision Support Systems (ODSS), challenges in analyzing user opinions, future of Sentiment Analysis, favorite books and more.
- New Book: Practical Data Science with R - Mar 29, 2014.
This new book will help you learn and apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.