Among both traditional carmakers and cutting-edge tech behemoths, there is massive competition to bring autonomous vehicles to market.
As the fourth industrial revolution approaches, factories can harness the power of machine learning to reduce maintenance costs.
At the end of April 2017, deepsense.ai released a new version of Neptune, the DevOps platform for data scientists. Neptune 1.5 introduces a range of new features and improvements, including support for Python 3, simplification of Neptune CLI, offline execution, …
In February we released a new version of Neptune, our machine learning platform for data scientists, supporting them in more efficient experiment management and monitoring. The latest 1.4 release introduces new features, like grid search — a hyperparameter optimization method and support for R and Java programming languages. Grid Search The first major feature introduced […]
We’re happy to announce that a new version of Neptune became available this month. The latest 1.3 release of deepsense.ai’s machine learning platform introduces powerful new features and improvements. This release’s key added features are: integration with TensorFlow and running Neptune experiments in Docker containers.
Underground mining poses a number of threats including fires, methane outbreaks or seismic tremors and bumps. An automatic system for predicting and alerting against such dangerous events is of utmost importance – and also a great challenge for data scientists and their machine learning models. This was the inspiration for the organizers of AAIA’16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Coal Mines.
deepsense.ai is releasing a new product. Neptune – a machine learning platform. Read about how we got the idea for Neptune and its main features.