This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
Many traditional businesses hate to fail. They embrace concepts such as Fail Fast in public, but deep inside their hearts, they are scared to fail.… Read More »Visually Explained: What Companies Get Wrong About Failure?
The Game Changer series By Stefan Dimitrov Stoyanov, Business Analytics Intern at Boemska As you may have noticed from my first and second articles about SAS… Read More »Using SAS Viya to Analyze Love at First Sight
Data scientist remains to be one of the best jobs in 2020. According to McKinsey, the US will be facing a shortfall of 250,000 data… Read More »A Pivotal Year for Data Scientists- 2020
Fifty years, ago, the lines between “data analysis” and “statistical analysis” were pretty clear. But as data analysis evolved, those lines became blurred. The differences… Read More »Difference between Data Analysis and Statistical Analysis
Summary: Workforce forecasting and scheduling applications are rapidly upgrading their use of AI. Techniques of time series forecasting ranging from the simple Holt Winters to… Read More »AI Techniques for Workforce Forecasting
News from Google. Across the web, there are millions of datasets about nearly any subject that interests you. If you’re looking to buy a puppy,… Read More »Finding Millions of Datasets with New Google Search Feature
There are many ways to deal with time-data. Sometimes one can use it as time-series to take possible trends into account. Sometimes this is not… Read More »How to make time-data cyclical for prediction?
Demand is the key indicator for every business to consider before taking the first step or expanding in the chosen market segment. It drives economic… Read More »The Complete Guide on Customer Demand Forecasting in Retail
In a meeting with engineering leadership, I was told, “We’ll tack on the AI later.” While doing ethnographic testing with a β customer, I was… Read More »Magic Dust for Artificial Intelligence Product Managers
Quantum computers come in 2 varieties, quantum annealers and quantum gate models. So far, DWave is the only company selling quantum annealers. A third type… Read More »So which is better for portfolio optimization, a NISQ Quantum Computer, or Fujitsu's "quantum inspired digital annealer"?
