Yupoo Picture Manager serves tens of millions of users and manages tens of billions of pictures. As its user gallery is growing larger, Yupoo has an urgent business need for a solution that can quickly locate the image. In other words, when a user inputs an image, the system should find its original…
Added by Kate Shao on August 12, 2020 at 11:00pm — No Comments
With the continuous development of network technology and the ever-expanding scale of e-commerce, the number and variety of goods grow rapidly and users need to spend a lot of time to find the goods they want to buy. This is information overload. To solve this problem, the recommendation system came into being.
The recommendation system is a…Continue
Added by Kate Shao on July 5, 2020 at 11:30pm — No Comments
Building accurate models takes a great deal of time, resources, and technical ability. The biggest challenge? You almost never know what model or feature combination will end…
Added by Benjamin Waxer on July 25, 2019 at 4:12am — No Comments
Summary: In the literal blink of an eye, image-based AI has gone from high cost, high risk projects to quick and reasonably reliable. C-level execs looking for AI techniques to exploit need to revisit their assumptions and move these up the list. Here’s what’s changed.
For data scientists these are miraculous times. We tend to think of miracles as something that occurs instantaneously but in our world that’s not quite so. Still the rate…Continue
Added by William Vorhies on March 4, 2019 at 9:41am — No Comments
Added by Kyrylo Kolodiazhnyi on January 21, 2019 at 7:44am — No Comments
In a previous blog post we have seen how to build Convolutional Neural Networks (CNN) in Tensorflow, by building various CNN architectures (like LeNet5, AlexNet, VGGNet-16) from scratch and training them on the MNIST, CIFAR-10 and Oxflower17 datasets.
It starts to get interesting when you start thinking about the practical applications of CNN and other Deep Learning methods. If you have been following the latest technical developments you probably know that CNN’s are…Continue
Added by Ahmet Taspinar on December 4, 2017 at 5:00am — No Comments
Summary: Which is more important, the data or the algorithms? This chicken and egg question led me to realize that it’s the data, and specifically the way we store and process the data that has dominated data science over the last 10 years. And it all leads back to Hadoop.
Summary: The addition of AI capabilities to our personal devices, applications, and even self-driving cars has caused us to take a much deeper look at what we call ‘User Experience’ (Ux). A more analytical framework identified as Cognitive Ergonomics is becoming an important field for data scientists to understand and implement.
Added by William Vorhies on October 31, 2017 at 9:51am — No Comments
Shahab Sheikh-Bahaei, Ph.D.*
Principal Data Scientist
Machine Learning (ML) is closely related to computational statistics which focuses on prediction-making through the use of computers. ML is a modern approach to an old problem: predictive inference. It makes an inference from “feature” space to “outcome/target” space.…Continue