Note from Udo Sglavo on mathematical optimization: When data scientists look at the essence of analytics and wonder about their daily endeavor, it often comes down to supporting better decisions. Peter F. Drucker, the founder of modern management, stated: "Whenever you see a successful business, someone once made a courageous decision."
In this article, we summarize our SAS research paper on the application of reinforcement learning to monitor traffic control signals which was recently accepted to the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada. This annual conference is hosted by the Neural Information Processing Systems Foundation, a non-profit corporation that promotes the exchange of ideas in neural information processing systems across multiple disciplines.
This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is “which algorithm should
Conversational AI can offer a way to provide that always-on 24/7, fast, convenient experience that can go anywhere (phone, computer smart speakers, even your car). It can provide a human-like experience through real-time, personalized interaction with AI running in the background. This technology is being applied across many industries for a variety of use cases (both customer-facing and for internal use).
In the second of a three-part series of posts, SAS' Funda Gunes and her colleague Ricky Tharrington summarize model-agnostic model interpretability in SAS Viya.
A monotonic relationship exists when a model’s output increases or stays constant in step with an increase in your model’s inputs. Relationships can be monotonically increasing or decreasing with the distinction based on which direction the input and output travel. A common example is in credit risk where you would expect someone’s risk score to increase with the amount of debt they have relative to their income.
Developing a loan approval application is a sensitive task since automatically approving loans to customers who will default can be costly for a lender. SAS enables quick and easy development and exposure of decision-making models from a single source. A simple and robust environment can make decisions less prone to errors.
In the first of a three-part series of posts, SAS' Funda Gunes and her colleague Ricky Tharrington summarize model-agnostic model interpretability in SAS Viya.
Let's talk about using DLPy to model employee retention through a survival analysis model. Survival analysis is used to model time-to-event. Examples of time-to-event include the time until an employee leaves a company, the time until a disease goes into remission, or the time until a mechanical part fails. The
Through hyperparameter autotuning, you can maximize a model's performance without maximizing effort. While SAS searches the hyperparameter space in the background, you are free to pursue other work.
