Table of Contents
What is TensorFlow and how do you use it?
TensorFlow ecosystem TensorFlow provides a collection of workflows to develop and train models using Python or JavaScript, and to easily deploy in the cloud, on-prem, in the browser, or on-device no matter what language you use. The tf. data API enables you to build complex input pipelines from simple, reusable pieces.
What is TensorFlow code?
Tensorflow: It is an end-to-end open-source platform managed and developed by Google for machine learning. Keras: It is also an open-source software library that provides a Python interface for deep learning neural networks. Keras acts as an interface for the Tensorflow Library.
Where do I put TensorFlow code?
The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup. Click the Run in Google Colab button.
What do I need to know before learning TensorFlow?
You should have good knowledge of algebra, statistics, basic calculus . And Python as programming language.
How do I open TensorFlow?
On Windows open the Start menu and open an Anaconda Command Prompt. On macOS or Linux open a terminal window. Use the default bash shell on macOS or Linux. Choose a name for your TensorFlow environment, such as “tf”.
How do you use keras and tensorflow in Jupyter notebook?
Setup Jupyter Notebook workspace with Tensorflow & Keras on…
- Install NuGet.
- Install a compatible python version.
- Create the Virtualenv.
- Activate the Virtualenv.
- Pip Install TensorFlow.
- Pip install Keras.
- Install Jupyter Notebook.
- Add env to ipykernel.
How do I find the tensorflow version of a Jupyter notebook?
To check your TensorFlow version in your Jupyter Notebook such as Google’s Colab, use the following two commands:
- import tensorflow as tf This imports the TensorFlow library and stores it in the variable named tf .
- print(tf. __version__) This prints the installed TensorFlow version number in the format x.y.z .