AI governance is an all-encompassing strategy that establishes oversight, ensures compliance and develops consistent operations and infrastructure within an organization. It also fosters a human-centric culture. This strategy includes specific governance domains such as data governance and model governance, necessary for a unified AI approach. Why AI governance matters The
This article discusses how to scale a probability density curve so that it fits appropriately on a histogram, as shown in the graph to the right. By definition, a probability density curve is scaled so that the area under the curve equals 1. However, a histogram might show counts or
Learn how to fit a random forest and use your model to score new data. In Part 6 and Part 7 of this series, we fit a logistic regression and decision tree to the Home Equity data we saved in Part 4. In this post we will fit a Random
“Generative AI is essentially just a subcategory of AI; it’s not that new algorithms have been invented.” Marinela Profi, AI Product Strategy Lead at SAS, says it up front and directly in her most recent podcast interview. “It takes a variety of data points, code, images and then, based on
Every June I try to write a blog post in honor of PRIDE month and in celebration of my wonderful LGBTQ+ colleagues, friends, and family members. This is for all the other parents and allies out there. It is about showing up. It is about aligning your words with your
In a previous blog post, we discussed how generative AI (GenAI) is experiencing unprecedented popularity, with organizations across various industries eager to unlock its immense potential. We also highlighted potential use cases organizations must identify to unlock GenAI's full potential with credit customer journeys. These can include using chatbots for
Presentation skills are an often-overlooked tool in the data scientist's box, and there's nothing like a room full of police to drive home the message that not everyone is a data geek. Police officers have a more visceral job than data scientists. Formulae, algorithms and methodologies aren't relevant to their
A previous article discusses a formula for a confidence interval for R-square in a linear regression model (Olkin and Finn (1995) "Correlations redux", Psychological Bulletin) The formula is useful for large data sets, but should be used with caution for small samples. At the end of the previous article, I
Mocktails are drinks that have all the flavor of traditional cocktails minus the alcohol. Whether you’re the designated driver, a non-drinker, looking to improve your health or simply seeking a refreshing sip, mocktails offer an elevated alternative for more conscious consumption.
SAS CMO Jennifer Chase and a panel of chief marketing officers offer insights on how they’re weaving AI into the business at American Marketing Association event Recent Salesforce research highlights a fact that didn’t seem to surprise the full-house audience at an American Marketing Association Annual CMO panel at SAS
Stop bias in its tracks – learn about the value of synthetic data for insurance.
A SAS analyst ran a linear regression model and obtained an R-square statistic for the fit. However, he wanted a confidence interval, so he posted a question to a discussion forum asking how to obtain a confidence interval for the R-square parameter. Someone suggested a formula from a textbook (Cohen,
Detecting illicit financial flows require much more than using traditional business methods. At this point, using centrality metrics in investigation and analytical models will provide wider detection approaches.
A recent SAS survey revealed that 80% of business leaders are anxious about GenAI's data privacy and security implications Owing to these and other concerns, Wells Fargo Chief Data Officer Brian Gibbons and an esteemed panel of AI experts, hosted by Wells Fargo Technology Banking, addressed an audience of the
SAS' Bahar Biller guides you through an asset lifetime prediction scenario using a synthetically generated historical data set and a solution built on SAS reliability modeling.
Synthetic data generation has intrigued across industries for its many use cases, including fraud detection, clinical trials, worker safety and law enforcement. One of the main benefits is the low cost of creating synthetic data, which is often cheaper than collecting actual demographic, psychographic or behavior-based information. With such data,
Step into the vibrant, insightful platform that is theCUBE, where industry leaders don’t just talk tech; they unpack AI’s impact on our world. Eight quotes aren’t enough to describe all the knowledge shared by SAS leaders during theCUBE’s session at SAS Innovate 2024. But this blog post would go on
Government employees charged with monitoring environmental compliance face a downpour of information, wading through countless reports and stacks of paperwork to accomplish their mission. To help these dedicated public servants increase productivity, agencies should consider a broader set of tools to control pollution, enforce regulations and improve compliance. Although foundational
A SAS analyst read my previous article about visualizing the predicted values for a regression model that uses spline effects. Because the original explanatory variable does not appear in the model, the analyst had several questions: How do you score the model on new data? The previous example has only
The new SAS Certified Specialist: Statistics for Machine Learning credential is designed to help you showcase your expertise and commitment to staying ahead in the industry.
Sometimes labels for variables get "dropped" during data preparation and cleaning. One example is when data are transposed from "wide form" to "long form." For example, suppose a data set has three variables, X, Y, and Z, each with labels. If you transpose the data to long form, the new
Batch manufacturing involves producing goods in batches rather than in a continuous stream. This approach is common in industries such as pharmaceuticals, chemicals, and materials processing, where precise control over the production process is essential to ensure product quality and consistency. One critical aspect of batch manufacturing is the need to manage and understand inherent time delays that occur at various stages of the process.
Remember when the popular catchphrase, “We have an app for that,” was the new big thing? You might not if you’re as young as the NC State University students who recently participated in the 11th annual SAS-NC State Design Project, but back when we could still count 21st-century years in
Skeletal muscle is important for so many reasons beyond movement or aesthetics. Muscle is a vital part of our metabolic and overall health, playing a key role in how we control glucose, insulin, energy levels and longevity.
A SAS programmer wanted to visualize density estimate for some univariate data. The data had several groups, so he wanted to create a panel of density estimate, which you can easily do by using PROC SGPANEL in SAS. However, the programmer's boss wanted to see filled density estimates, such as
Generative AI (GenAI) is in its most popular era and many organisations across industry are looking for ways to unlock its potential value. McKinsey's projections suggest that GenAI could add a staggering $2.6 to $4.4 trillion in value to the global economy. In fact, banking is the number one industry
Across the world, investigators and law enforcement officers are tackling a rapidly evolving and expanding workload fueled by an increase in complex modern-day crimes. As technology alters the type and methodology of the crime itself – the evasion of tax payments, theft of public funds, erroneous disbursement of benefits, gaming
Our employees’ health and well-being is important to us, so we make sure that they – and their families – have access to facilities and programs promoting fitness, wellness and recreation. That’s why our headquarters campus has 28 acres dedicated to the physical fitness of employees (and that doesn’t include
After writing a program that simulates data, it is important to check that the statistical properties of the simulated (synthetic) data match the properties of the model. As a first step, you can generate a large random sample from the model distribution and compare the sample statistics to the expected
Imagine stuffing a 500,000-square-foot event space into a 5,000-square-foot hallway. That was the crazy idea I had when I checked out the Innovation Hub. The Innovation Hub was the center of the action at SAS Innovate in Las Vegas. Attendees saw demos of the hottest new SAS solutions, met the technical
