Training XGBoost with R and Neptune

We present the training of an XGBoost model and evaluation of the results in an example analysis of bank customer data, using R with Neptune. helps improve the UK’s satellite defence and security intelligence helps improve the UK’s satellite defence and security intelligence

The team makes a significant contribution to the satellite imagery project hosted at aimed at increasing the efficiency of the decision-making process for the UK’s defence and security.

Why allow Cloudera’s vendor locking instead of using’s Neptune?

Why allow Cloudera’s vendor locking instead of using’s Neptune? congratulates Cloudera on acquiring and their recent launch of the Cloudera Data Science Workbench. “Well done, but too late!” – says’s CEO Tomasz Kulakowski, and asks: “Why allow Cloudera’s vendor locking instead of using’s Neptune – a DevOps platform for machine and deep learning experiments, which works with any Hadoop distribution (incl. Hortonworks, Cloudera and MapR) and any cloud provider (such as AWS, MS Azure, Google Cloud Platform) as well as available on-premises?”

Neptune machine learning platform: grid search, R & Java support

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 […]