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authorGravatar Vijay Vasudevan <vrv@google.com>2015-11-18 10:47:35 -0800
committerGravatar Vijay Vasudevan <vrv@google.com>2015-11-18 10:47:35 -0800
commitab34d55ce7618e52069a2e1c9e51aac5a1ea81c3 (patch)
tree9c79427b45ff6501e8374ceb7b4fc3bdb2828e15 /tensorflow/g3doc/get_started/index.md
parent9eb88d56ab6a9a361662d73a258593d8fbf10b62 (diff)
TensorFlow: more features, performance improvements, and doc fixes.
Changes: - Add Split/Concat() methods to TensorUtil (meant for convenience, not speed) by Chris. - Changes to linear algebra ops interface by Rasmus - Tests for tensorboard by Daniel - Fix bug in histogram calculation by Cassandra - Added tool for backwards compatibility of OpDefs. Tool Checks in history of opdefs and their changes, checks for backwards-incompatible changes. All done by @josh11b - Fix some protobuf example proto docs by Oliver - Add derivative of MatrixDeterminant by @yaroslavvb - Add a priority queue queue by @ebrevdo - Doc and typo fixes by Aurelien and @dave-andersen - Speed improvements to ConvBackwardFilter by @andydavis - Improve speed of Alexnet on TitanX by @zheng-xq - Add some host memory annotations to some GPU kernels by Yuan. - Add support for doubles in histogram summary by @jmchen-g Base CL: 108158338
Diffstat (limited to 'tensorflow/g3doc/get_started/index.md')
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diff --git a/tensorflow/g3doc/get_started/index.md b/tensorflow/g3doc/get_started/index.md
index 0c58b969c7..3fce5e9d89 100644
--- a/tensorflow/g3doc/get_started/index.md
+++ b/tensorflow/g3doc/get_started/index.md
@@ -1,4 +1,4 @@
-# Introduction <a class="md-anchor" id="AUTOGENERATED-introduction"></a>
+# Introduction
Let's get you up and running with TensorFlow!
@@ -43,6 +43,10 @@ for step in xrange(0, 201):
# Learns best fit is W: [[0.100 0.200]], b: [0.300]
```
+The first part of this code builds the data flow graph. TensorFlow does not
+actually run any computation until the session is created and the `run`
+function is called.
+
To whet your appetite further, we suggest you check out what a classical
machine learning problem looks like in TensorFlow. In the land of neural
networks the most "classic" classical problem is the MNIST handwritten digit
@@ -67,7 +71,7 @@ these and charge ahead. Don't worry, you'll still get to see MNIST -- we'll
also use MNIST as an example in our technical tutorial where we elaborate on
TensorFlow features.
-## Recommended Next Steps: <a class="md-anchor" id="AUTOGENERATED-recommended-next-steps-"></a>
+## Recommended Next Steps:
* [Download and Setup](../get_started/os_setup.md)
* [Basic Usage](../get_started/basic_usage.md)
* [TensorFlow Mechanics 101](../tutorials/mnist/tf/index.md)