TensorFlow development environment setup with Anaconda (windows)

TensorFlow is an open-source software library for data flow programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. It is used for both research and production at Google.‍

It is broad used by world level enterprises, and the best open source library for individual developer to explore this area.

The open source Anaconda Distribution is the fastest and easiest way to do Python and R data science and machine learning on Linux, Windows, and Mac OS X. It’s the industry standard for developing, testing, and training on a single machine.

Here I will introduce how to install TensorFlow with Anaconda.

Install Anaconda latest version which is Python 3.7 version

By the way, before installing of TensorFlow, make sure your OS and Machine are all 64 bits, which is the basic requirement from TensorFlow.
After installation of Anaconda, please run the Anaconda Promote from start menu with administrator authority, which is the command line console.

It already supported the virtual environment.

Downgrade Anaconda to Python 3.6.8

Since the TensorFlow cannot support Python 3.7, we need to downgrade Anaconda to 3.6.8 first.
By using command line

conda install python=3.6.8

Then waiting for the solving environment finished

Install TensorFlow by pip

By using command line

pip install --upgrade pip

to upgrade the pip, then install TensorFlow

pip install --upgrade tensorflow

If installation failed, you can use

pip install --ignore-installed tensorflow

to force reinstall.

Finally using

python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"

to verify installation success