Microsoft Cognitive Toolkit v2.0 now available for download

The Microsoft Cognitive Toolkit, previously known as CNTK, allows developers to harness the intelligence within massive datasets through deep learning by providing scaling, speed and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms you already use. Microsoft yesterday announced the release of updated version of Microsoft Cognitive Toolkit. Microsoft Cognitive Toolkit version 2.0 includes hundreds of new features, performance improvements and bug fixes. Find the list of new features added in this release below.

• The ability to extend Cognitive Toolkit functions, learners, trainers and optimizers with your own algorithms in Python, C++.
• Enhanced, built-in distributed readers for speech, image, and text deep learning tasks.
• The ability to use TensorBoard visualizations from Cognitive toolkit! Read more here.
• Pretrained models available for use.
• Performance improvements.
• Support of distributed scenarios in Python API. See more in the sections on distributed scenarios in the ConvNet and ResNet examples.
• Support of Asynchronous Stochastic Gradient Descent (ASGD)/Hogwild! training parallelization support using Microsoft's Parameter Server (Project Multiverso).
• Support for training on one-hot and sparse arrays via NumPy.
• Support of object recognition using Fast R-CNN algorithm.
• Integration with NVIDIA NCCL, a stand-alone library of standard collective communication routines, such as all-gather, reduce, broadcast, etc., that have been optimized to achieve high bandwidth over PCIe. See how to enable NCCL in the Cognitive Toolkit Wiki.
• Lambda rank and NDCG at 1 are accessible from Python for real this time.
• Performance Profiler for BrainScript and Python.
• Support in training session for cross validation and preservation of all checkpoints.

You can read about all the changes that will be part of this v2.0 update here. And you can download the Microsoft Cognitive Toolkit v2.0 here.

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