How to Install TensorFlow in Jupyter Notebook

As a data scientist, you may have heard about the powerful machine learning framework called TensorFlow. TensorFlow is an open-source software library developed by Google that allows you to build and train machine learning models. In this blog post, we will show you how to install TensorFlow in Jupyter Notebook, a popular web-based interactive development environment for data science.

Step 1: Install Anaconda

Before we begin installing TensorFlow, we need to install Anaconda, a popular Python distribution that includes Jupyter Notebook. You can download the latest version of Anaconda from the official website: https://www.anaconda.com/products/individual.

Once the download is complete, follow the installation instructions for your operating system. After the installation is complete, open Anaconda Navigator.

Step 2: Create a new environment

To avoid conflicts with other Python packages, we recommend creating a new environment specifically for TensorFlow. In Anaconda Navigator, click on the “Environments” tab and then click on “Create”. Give your new environment a name, such as “tensorflow_env”, and choose the Python version you want to use.

Step 3: Install TensorFlow

With our new environment created, we can now install TensorFlow. There are two ways to install TensorFlow: using pip or using conda. We recommend using conda as it will automatically install all the necessary dependencies.

In Anaconda Navigator, select your new environment and click on “Open Terminal”. This will open a terminal window with your new environment activated. Type the following command to install TensorFlow:

conda install tensorflow

This will download and install the latest version of TensorFlow in your environment.

Step 4: Install Jupyter Notebook

Now that we have TensorFlow installed, we need to install Jupyter Notebook so we can start using it. In the same terminal window, type the following command:

conda install jupyter

This will download and install Jupyter Notebook in your environment.

Step 5: Launch Jupyter Notebook

With TensorFlow and Jupyter Notebook installed, we can now launch Jupyter Notebook. In the same terminal window, type the following command:

jupyter notebook

This will open Jupyter Notebook in your default web browser. You should see a list of files and folders in your home directory. To create a new notebook, click on the “New” button in the top right corner and select “Python 3” under “Notebooks”.

Step 6: Test TensorFlow

To test if TensorFlow is working correctly, we can create a simple program that adds two numbers using TensorFlow. In your new notebook, type the following code:

import tensorflow as tf

a = tf.constant(2)
b = tf.constant(3)

c = tf.add(a, b)

with tf.Session() as sess:
    result = sess.run(c)
    print(result)

This program creates two constants, “a” and “b”, and adds them together using TensorFlow’s “add” function. The result is then printed to the console.

To run the program, click on the “Run” button in the toolbar or press “Shift+Enter”. You should see the result, “5”, printed to the console.

Congratulations, you have successfully installed TensorFlow in Jupyter Notebook!

Conclusion

In this blog post, we have shown you how to install TensorFlow in Jupyter Notebook using Anaconda. By following these simple steps, you can start building and training machine learning models using TensorFlow in Jupyter Notebook. Remember to create a new environment specifically for TensorFlow to avoid conflicts with other Python packages.