The number of data scientists has grown over 650% over the past five years. Machine learning and deep learning skills are in huge demand at present, and the list of reasons you should join those already working in the profession is broad.
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.
Tired of overly theoretical introductions to deep learning? Experiment hands-on with CIFAR-10 image classification with Keras by running code in Neptune.
We’ve open sourced image classification sample solution that lets data scientists start competing in the currently running Kaggle Cdiscount competition.
Monitoring brand visibility is an important business problem. We describe our solution for logo detection and visibility analytics with deep learning.
We apply three different deep learning models to reproduce state-of-the-art results in single image super resolution.
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.
We present the result of research conducted at deepsense.ai, that focuses on distributing a reinforcement learning algorithm to train on a large CPU cluster
Everybody who watched ‘Minority Report’ daydreams about crime forecasting in the real world. We have good news: machine learning algorithms can do that!
Deep learning vs human perception: creating a log loss benchmark for industrial & medical image classification problems (e.g. cancer screening).