← Back to Blog

Install Keras on Anaconda OSX: A Guide for Data Scientists

Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It’s user-friendly, modular, and extensible, making it a popular choice for data scientists. This guide will walk you through the process of installing Keras on Anaconda OSX, a powerful package manager and environment management system.
By Saturn Cloud | | Miscellaneous

Install Keras on Anaconda OSX: A Guide for Data Scientists

Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It’s user-friendly, modular, and extensible, making it a popular choice for data scientists. This guide will walk you through the process of installing Keras on Anaconda OSX, a powerful package manager and environment management system.

Prerequisites

Before we begin, ensure you have Anaconda installed on your OSX system. If not, you can download it from the official Anaconda website.

Step 1: Create a New Anaconda Environment

Creating a new environment helps isolate your project and avoid conflicts with other packages. Use the following command to create a new environment named ‘keras_env’:

conda create -n keras_env python=3.7

Activate the environment with:

conda activate keras_env

Step 2: Install Keras

With the environment activated, you can now install Keras. Anaconda makes this process straightforward with the following command:

conda install -c conda-forge keras

This command tells Anaconda to install Keras from the Conda-Forge channel, a community-led collection of packages.

Step 3: Verify the Installation

After the installation process, it’s good practice to verify that Keras was installed correctly. You can do this by starting Python within your Anaconda environment and attempting to import Keras:

python
>>> import keras

If you don’t receive any error messages, congratulations! You’ve successfully installed Keras on Anaconda OSX.

Step 4: Install TensorFlow Backend

While Keras can run on multiple backends, TensorFlow is the most popular. To install TensorFlow, use the following command:

conda install -c conda-forge tensorflow

Step 5: Test Keras with TensorFlow Backend

Finally, let’s test Keras with the TensorFlow backend. Start Python and run the following commands:

>>> from keras import backend as K
>>> K.tensorflow_backend._get_available_gpus()

If everything is set up correctly, this command should return the list of available GPUs.

Conclusion

Installing Keras on Anaconda OSX is a straightforward process that can be completed in just a few steps. By creating a dedicated environment, you can ensure that your Keras setup won’t interfere with other projects and can be easily replicated or shared with others.

Keras is a powerful tool for data scientists, offering a high-level, user-friendly API for creating and training neural networks. With Keras installed on your Anaconda OSX system, you’re ready to start building and training your own neural networks.

Remember, the key to mastering any tool is practice. So, start experimenting with different models and datasets, and don’t be afraid to make mistakes. Happy coding!

Keywords

  • Keras
  • Anaconda OSX
  • TensorFlow
  • Neural Networks
  • Data Scientists
  • Installation Guide
  • Python
  • Conda-Forge
  • Environment Management
  • Package Manager

Meta Description

A comprehensive guide for data scientists on installing Keras, a high-level neural networks API, on Anaconda OSX. Includes step-by-step instructions and verification process.

About Saturn Cloud

Saturn Cloud is your all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, and more. Join today and get 150 hours of free compute per month.

Try Saturn Cloud Now