谷歌第二代機器學習系統，TensorfFlow 0.6.0 發布
TensorFlow 是谷歌的第二代機器學習系統，按照谷歌所說，在某些基準測試中，TensorFlow的表現比第一代的DistBelief快了2倍。
TensorFlow 內建深度學習的擴展支持，任何能夠用計算流圖形來表達的計算，都可以使用TensorFlow。任何基于梯度的機器學習算法都能夠受益于TensorFlow的自動分 化（auto-differentiation）。通過靈活的Python接口，要在TensorFlow中表達想法也會很容易。
TensorFlow 對于實際的產品也是很有意義的。將思路從桌面GPU訓練無縫搬遷到手機中運行。
TensorfFlow 0.6.0 發布，更新如下：主要特性和提升
-
Python 3.3+ support via changes to python codebase and ability to specify python version via ./configure.
-
Some improvements to GPU performance and memory usage:convnet benchmarksroughly equivalent with native cudnn v2 performance. Improvements mostly due to moving to 32-bit indices, faster shuffling kernels. More improvements to come in later releases.
Bug 修復
-
Lots of fixes to documentation and tutorials, many contributed by the public.
-
271 closed issues on github issues.
向后兼容變化
-
tf.nn.fixed_unigram_candidate_sampler changed its default 'distortion' attribute from 0.0 to 1.0. This was a bug in the original release that is now fixed.
更多內容請看：
https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md