How to Install Tensorflow and Keras in Jupyter Notebook (Easy Method)

If you are interested in using TensorFlow and Keras for your machine learning projects, installing them in a Jupyter Notebook is a convenient way to get started. In this article, we will show you an easy method to install TensorFlow and Keras in Jupyter Notebook.

Step 1: Install Anaconda

The first step is to install Anaconda, which is a popular Python distribution that comes with many pre-installed packages for data science and machine learning. You can download and install Anaconda from the official website.

Step 2: Create a New Conda Environment

Once Anaconda is installed, open a new terminal and create a new conda environment for your project using the following command:

conda create -n myenv python=3.7

Replace “myenv” with the name you want for your environment, and “python=3.7” with the Python version you want to use.

Step 3: Activate the Conda Environment

After creating the conda environment, you can activate it using the following command:

conda activate myenv

Step 4: Install TensorFlow and Keras

With the conda environment activated, you can now install TensorFlow and Keras using pip:

pip install tensorflow keras

Step 5: Open Jupyter Notebook

Finally, you can open Jupyter Notebook and start using TensorFlow and Keras in your projects. Simply type “jupyter notebook” in the terminal to launch Jupyter Notebook, and create a new notebook to start writing your machine learning code.

Conclusion

By following these easy steps, you can install TensorFlow and Keras in a Jupyter Notebook and start building your machine learning models with ease. This method is convenient and straightforward, making it ideal for beginners and experienced developers alike.