To introduce TensorFlow, it is vital to have "Python" introduced in your framework. Python rendition 3.4+ is viewed as the best to begin with TensorFlow establishment.
Consider the accompanying strides to introduce TensorFlow in Windows working framework.
Stage 1 − Verify the python form being introduced.
Stage 2 − A client can get any component to introduce TensorFlow in the framework. We suggest "pip" and "Boa constrictor". Pip is an order utilized for executing and introducing modules in Python. Before we introduce TensorFlow, we really want to introduce Anaconda structure in our framework. After successful installation, check in command prompt through “conda” command.
Step 3 − Execute the following command to initialize the installation of TensorFlow −
conda create --name tensorflow python = 3.5
Step 4 − After successful environmental setup, it is important to activate TensorFlow module.
Step 5 − Use pip to install “Tensorflow” in the system. The command used for installation is mentioned as below −
pip install tensorflow
After successful installation, it is important to know the sample program execution of TensorFlow.
pip install tensorflow-gpu
write simple program which helps us understand the basic program creation “Hello World” in TensorFlow.
The code for first program implementation is mentioned below −
>> activate tensorflow
>> python (activating python shell>
>> import tensorflow as tf >> hello = tf.constant(‘Hello, Tensorflow!’>
>> sess = tf.Session(>
TensorFlow NVIDIA NGC here
Does Python 2.7 support TensorFlow?
The TensorFlow Python API supports Python 2.7 and Python 3.3+.
Is TensorFlow 2.6 stable?
0 Now Available. The freshest form of TensorFlow is a stability delivery and brings various significant highlights, enhancements, bug fixes and different changes.
Is TensorFlow allowed to download?
TensorFlow is a free and open-source programming library for AI and computerized reasoning.