In this latest Data Science Central webinar, we will introduce and demonstrate how you can perform common time-series Machine Learning tasks such as Forecasting and Anoma...
On average, 80% of AI projects fail to make it to production. But it IS possible to successfully launch AI, at scale, that is built responsibly and works for everyone. Ho...
It’s been two years since Mckinsey invented the term analytics translator, called it the ‘new must-have role’ and predicted we’d need around 5 million of th...
Summary: What is an AI Product Manager and how do you know when you need one. The role of Product Manager (PM) can mean many things dependent on the specifics of the co...
The challenge with data search The explosion in unstructured data, such as images, videos, sound records, and text, requires an effective solution for computer vision, vo...
Fundamentals of PyTorch – Introduction Since it was introduced by the Facebook AI Research (FAIR) team, back in early 2017, PyTorch has become a highly popular and wid...
Interested in learning how to build and deploy modern optimization applications that deliver tremendous business value? In this latest Data Science Central webinar, you w...
Summary: In a comprehensive study of 18 recently presented DNN advancements in top-N recommenders, only 7 presented sufficient data to allow reproduction. Worse, of t...
In supervised machine learning algorithms, Random Forest stands apart as it is arguably the most powerful classification model. When Microsoft developed their X-box game ...
It’s generally accepted that you need a team with a wide variety of skills to build modern machine learning (ML) pipelines and make them operational. But what does ...