TensorFlow Jobs: Interview Questions

TensorFlow Jobs: Interview Questions

What are the key features of TensorFlow?

• Efficiently works with mathematical expressions involving multi-dimensional arrays
• Good support of deep neural networks and machine learning concepts
• GPU/CPU computing where the same code can be executed on both architectures
• High scalability of computation across machines and huge data sets

How to Install?

• We will be using the TensorFlow Python API, which works with Python 2.7 and Python 3.3+. The GPU version (Linux only) requires the Cuda Toolkit 7.0+ and cuDNN v2+.
• We shall use the Conda package dependency management system to install TensorFlow. Conda allows us to separate multiple environments on a machine.
• The Python version installed inside this environment is 2.7, and we will use this version in this article.

conda create --name TensorflowEnv biopython

To make things easy, we are installing python here instead of just NumPy. This includes NumPy and a few other packages that we will be needing. You can always install the packages as you need them using the conda install or the pip install commands.

The following command will activate the created Conda environment. We will be able to use packages installed within it, without mixing with packages that are installed globally or in some other environments.

source activate TensorFlowEnv

The pip installation tool is a standard part of a Conda environment. We will use it to install the TensorFlow library. Prior to doing that, a well the first step is updating pip to the latest version, using the following command:

pip install --upgrade pip

Now we are ready to install TensorFlow, by running:

pip install tensorflow

The download and build of TensorFlow can take several minutes. At the time of writing, this installs TensorFlow 1.1.0.