Deep Learning: Which Loss and Activation Functions should I use? The purpose of this post is to provide guidance on which combination of final-layer activation function and loss function should be used in a neural [...]
Summary: If Deep Learning is powered by 2nd generation neural nets. What will the 3rd generation look like? What new capabilities does that imply and when will it get here? By far the fastest expanding frontier of [...]
A Big Data Center collaboration between computational scientists at Lawrence Berkeley National Laboratory’s (Berkeley Lab) National Energy Research Scientific Computing Center (NERSC) and engineers at Intel and Cray has yielded another first in the quest to apply [...]
ODSC East - Boston - May 1-4 2018 ThirdEye is pleased to announce its partnership with Open Data Science Conference (ODSC) and announce the ODSC East event in Boston fromMay 1st through May 4th [...]
Overview Theano is a Python library for fast numerical computation that can be run on the CPU or GPU. It is a key foundational library for Deep Learning in Python that you can use [...]
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD [...]
TensorFlow Architecture We designed TensorFlow for large-scale distributed training and inference, but it is also flexible enough to support experimentation with new machine learning models and system-level optimizations. This document describes the system architecture [...]
Machine learning projects are creating a ‘once-in-a-lifetime opportunity’ for partners. Get ready with the right range of skills and experience to take part. […]
