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Updated MAC install instructions for Anaconda w/ python 3
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‎README.md‎

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@@ -361,37 +361,31 @@ Successfully installed h5py-2.7.0
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## Mac Setup
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### Installing Python
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### Pre-work with older Anaconda installs
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Install Homebrew https://brew.sh/
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brew install python
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> cn ~ $ rm -rf ~/anaconda2
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### Installing Pip
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Remove the export for this install
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> cn ~ $ vi ~.bash_profile
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Anaconda was already setup... from an older Continuium Download so this area needs to be re-worked from a scatch build.
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* Python 2.7.12 :: Anaconda custom (x86_64)
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> cn ~ $ pip -V
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```bash
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pip 8.1.1 from /Users/cn/anaconda/lib/python2.7/site-packages (python 2.7)
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### Installing Python w/ Anaconda
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* Download the bash script from https://www.continuum.io/downloads#macos
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* I'm using the latest version for python 3... since I had issues with some older libs with python2
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```
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cd Downloads
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> bash Anaconda3-4.3.1-MacOSX-x86_64.sh
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> cn ~ $ sudo easy_install --upgrade pip
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>
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```bash
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### Verify Python & Pip Installs
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> cn ~ $ python -V | pip -V
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Best match: pip 9.0.1
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```
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> cn ~ $ pip -V
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```bash
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pip 9.0.1 from /Users/cn/anaconda/lib/python2.7/site-packages/pip-9.0.1-py2.7.egg (python 2.7)
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```bash
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Python 3.6.0 :: Anaconda 4.3.1 (x86_64)
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pip 9.0.1 from /Users/cn/anaconda3/lib/python3.6/site-packages (python 3.6)
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```
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### Install Tensorflow
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> cn ~ $ python
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```bash
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Python 2.7.12 |Anaconda custom (x86_64)| (default, Jul 2 2016, 17:43:17)
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[GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.11.00)] on darwin
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Python 3.6.0 |Anaconda 4.3.1 (x86_64)| (default, Dec 23 2016, 13:19:00)
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[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] on darwin
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Type "help", "copyright", "credits" or "license" for more information.
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Anaconda is brought to you by Continuum Analytics.
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Please check out: http://continuum.io/thanks and https://anaconda.org
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>>> import tensorflow tf
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File "<stdin>", line 1
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import tensorflow tf
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^
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SyntaxError: invalid syntax
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>>> import tensorflow as tf
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>>> hello = tf.constant('Hello, TensorFlow!')
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>>> sess = tf.Session()
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>>> sess = tf.Session()
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W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions,
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but these are available on your machine and could speed up CPU computations.
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W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions,
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but these are available on your machine and could speed up CPU computations.
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W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions,
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but these are available on your machine and could speed up CPU computations.
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W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions,
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but these are available on your machine and could speed up CPU computations.
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W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions,
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but these are available on your machine and could speed up CPU computations.
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2017-05-08 20:29:44.953858: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
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2017-05-08 20:29:44.953899: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
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2017-05-08 20:29:44.953912: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
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2017-05-08 20:29:44.953925: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
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2017-05-08 20:29:44.953936: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
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>>> print(sess.run(hello))
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Hello, TensorFlow!
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b'Hello, TensorFlow!'
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```
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cn ~ $ python -c 'import tensorflow as tf; print(tf.__version__)' # for Python 2
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1.0.1
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#### Check the Version of TensorFlow
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cn ~ $ python -c 'import tensorflow as tf; print(tf.__version__)'
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1.1.0
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### Test numpy, scipy
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> cn ~ $ python
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```python
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Python 2.7.12 |Anaconda custom (x86_64)| (default, Jul 2 2016, 17:43:17)
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[GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.11.00)] on darwin
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Python 3.6.0 |Anaconda 4.3.1 (x86_64)| (default, Dec 23 2016, 13:19:00)
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[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] on darwin
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Type "help", "copyright", "credits" or "license" for more information.
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Anaconda is brought to you by Continuum Analytics.
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Please check out: http://continuum.io/thanks and https://anaconda.org
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>>> import scipy
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>>> import numpy
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>>> scipy.__version__
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'0.15.0'
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'0.18.1'
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>>> numpy.__version__
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'1.12.1'
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'1.11.3'
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>>> quit()
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```
@@ -455,24 +445,52 @@ Please check out: http://continuum.io/thanks and https://anaconda.org
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> cn ~ $ pip install --upgrade keras
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Make TensorFlow the default engine for Keras
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### Make Sure Keras runs
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```bash
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Collecting keras
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Downloading Keras-2.0.4.tar.gz (199kB)
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100% |████████████████████████████████| 204kB 342kB/s
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Collecting theano (from keras)
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Downloading Theano-0.9.0.tar.gz (3.1MB)
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100% |████████████████████████████████| 3.1MB 108kB/s
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Requirement already up-to-date: pyyaml in ./anaconda3/lib/python3.6/site-packages (from keras)
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Requirement already up-to-date: six in ./anaconda3/lib/python3.6/site-packages (from keras)
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Collecting numpy>=1.9.1 (from theano->keras)
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Downloading numpy-1.12.1-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (4.4MB)
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100% |████████████████████████████████| 4.4MB 126kB/s
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Collecting scipy>=0.14 (from theano->keras)
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Downloading scipy-0.19.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (16.2MB)
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100% |████████████████████████████████| 16.2MB 40kB/s
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Building wheels for collected packages: keras, theano
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Running setup.py bdist_wheel for keras ... done
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Stored in directory: /Users/cn/Library/Caches/pip/wheels/48/82/42/f06a8c03a8f95ada523a81ba723e89f059693e6ad868d09727
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Running setup.py bdist_wheel for theano ... done
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Stored in directory: /Users/cn/Library/Caches/pip/wheels/d5/5b/93/433299b86e3e9b25f0f600e4e4ebf18e38eb7534ea518eba13
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Successfully built keras theano
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Installing collected packages: numpy, scipy, theano, keras
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Found existing installation: numpy 1.11.3
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Uninstalling numpy-1.11.3:
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Successfully uninstalled numpy-1.11.3
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Found existing installation: scipy 0.18.1
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Uninstalling scipy-0.18.1:
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Successfully uninstalled scipy-0.18.1
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Successfully installed keras-2.0.4 numpy-1.12.1 scipy-0.19.0 theano-0.9.0
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```
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> cn ~ $ python
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```bash
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Python 2.7.12 |Anaconda custom (x86_64)| (default, Jul 2 2016, 17:43:17)
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[GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.11.00)] on darwin
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cn ~ $ python
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Python 3.6.0 |Anaconda 4.3.1 (x86_64)| (default, Dec 23 2016, 13:19:00)
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[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] on darwin
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Type "help", "copyright", "credits" or "license" for more information.
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Anaconda is brought to you by Continuum Analytics.
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Please check out: http://continuum.io/thanks and https://anaconda.org
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>>> import keras; keras.__version__
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>>> import keras
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Using TensorFlow backend.
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'2.0.4'
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>>> quit()
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```
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[Blog](https://ermaker.github.io/blog/2016/06/22/get-started-with-keras-for-beginners-tensorflow-backend.html)
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> cn ~ $ curl -sSL https://github.com/fchollet/keras/raw/master/examples/mnist_mlp.py | python
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If this script runs... everything is working.
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