Deloitte estimates that in 2021 enterprise spending on artificial intelligence and machine learning projects will reach 57 billion dollars
German team – the one Goldman Sachs picked with predictive analytics as the probable world champ – failed to get out of its group for the first time in 80 years.
Although machine learning is seen as a monolith, this cutting-edge technology is diversified, with various sub-types including machine learning, deep learning, and the state-of-the-art technology of deep reinforcement learning.
Keras and PyTorch are both excellent choices for your first deep learning framework. Learn how they differ and which one will suit your needs better.
Software that understands muscle-controlled limb movement would be able to translate neural signals into instructions for automated arms or legs.
From countering an invasion of aliens to demolishing a wall with a ball – AI outperforms humans after just 20 minutes of training.
Harnessing the power of AI’s image recognition and deep learning may significantly reduce the cost of visual quality control.
deepsense.ai ML team has been working with Google Brain on helping AI imagine and reason about the future. They started from optimizing TensorFlow’s infrastructure for reinforcement learning and moved to end-to-end training of AI entirely on Google’s newest Cloud TPUs.
Monitoring brand visibility is an important business problem. We describe our solution for logo detection and visibility analytics with deep learning.
We’re thrilled today to announce the latest version of Neptune: Machine Learning Lab. This release will allow data scientists using Neptune to take some giant steps forward. Here we take a quick look at each of them.