- Large cleanup to add second order gradient for ops with C++ gradients and improve existing gradients such that most ops can now be differentiated multiple times.
- TensorFlow now builds and runs on Microsoft Windows (tested on Windows 10, Windows 7, and Windows Server 2016).
- Improve trace, matrix_set_diag , matrix_diag_part and their gradients to work for rectangular matrices.
- Added a new library for library of matrix-free (iterative) solvers for linear equations, linear least-squares, eigenvalues and singular values in tensorflow/contrib/solvers.
- C API: Type TF_SessionWithGraph has been renamed to TF_Session , indicating its preferred use in language bindings for TensorFlow.
tensorflow – Computation using data flow graphs for scalable machine learning
Continue reading “Release TensorFlow v0.12.0 RC0 · tensorflow/tensorflow · GitHub”
- Deep learning course: Getting Started with the Caffe Framework
- Choose a deep learning framework from the list below, download the supported version of cuDNN and follow the instructions on the framework page to get started.
- Chainer is a deep learning framework that’s designed on the principle of define-by-run.
- Caffe is a deep learning framework made with expression, speed, and modularity in mind.
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@GPUComputing: “New #cuDNN 5.1, 2.7x faster training of #deeplearning networks with 3×3 convolutions.”
The NVIDIA Deep Learning SDK accelerates widely-used deep learning frameworks such as Caffe, CNTK, TensorFlow, Theano and Torch as well as many other deep learning applications. Choose a deep learning framework from the list below, download the supported version of cuDNN and follow the instructions on the framework page to get started.
Deep Learning Frameworks