Download tensorflow version

Select Check for updates in the Windows Update section of the Settings app. We recommend setting up a virtual Python environment inside Windows. There are many tools that you can use to set up a virtual Python environment—for these instructions, we'll use Anaconda's Miniconda. The rest of this setup assumes that you use a Miniconda environment.

Download and install the Miniconda Windows installer on your system. There is additional guidance for setup on Anaconda's site. Once Miniconda is installed, create an environment using Python named directml , and activate it through the following commands. Watch all the sessions on demand View sessions. Requires the latest pip pip install --upgrade pip Current stable release for CPU and GPU pip install tensorflow Or try the preview build unstable pip install tf-nightly. Download a package Install TensorFlow with Python's pip package manager.

Official packages available for Ubuntu, Windows, and macOS. Read the pip install guide. Read the Docker install guide. Google Colab: An easy way to learn and use TensorFlow No install necessary—run the TensorFlow tutorials directly in the browser with Colaboratory , a Google research project created to help disseminate machine learning education and research.

Web developers TensorFlow. So, your friend doesn't want to update the library to 1. An environment solves this problem by allowing your friend to have both versions of the library, 1. Let's create an environment for our data science development, we'll call this environment dataweekends , but you can call it with any name you want. If all goes to plan at the end you should see this message:.

This will prepend dataweekends to your terminal prompt. You can verify that you are in the correct active environment by typing:. We have created an environment and successfully activated it. Now let's install keras. Version 1. There are several ways to install it, we'll use the pip method for this tutorial. In your active dataweekends environment terminal type:.

Keras is a high-level neural networks api specification, implemented in Python and capable of running on top of either TensorFlow or Theano.

It was developed with a focus on enabling fast experimentation and it allows to go from idea to result with the least possible delay. Although Keras is also provided by community channel of Anaconda packages conda-forge , it's most recent version is best installed with pip , so we'll go ahead and use that version.

At the time of writing this installs keras version 1. Also, at the Tensorflow Dev Summit it was announced that keras will become part of Tensorflow from version 1.

You have successfully set up your Mac for development with Python, Keras and Tensorflow! If you are not sure about the version of a Tensorflow or any other package , it's easy to check that. In the ipython console make sure you started it from within your environment. Keras' backend is set in a hidden file stored in your home path.

You can open it with a text editor and you should see something like this:. Switching backend is as easy as replacing tensorflow with theano in the last key. Then save the file and close it. If you then open ipython and import keras you should see:. Compute Capabilities version identify the features supported my the GPU. First, you need to know your video card. Then you need to see if the card is supported by CUDA by finding you card here: Now you have hardware support confirmed, let us move forward and install the driver.

TensorFlow as a Cake Addin addin nuget:? TensorFlow as a Cake Tool tool nuget:? TensorFlow contains ML. NET integration of TensorFlow. NETStandard 2. TensorFlow: Package Downloads Microsoft. Vision Microsoft. MachineLearning Simple machine learning wrapper for Microsoft.