Keras is a high-level, neural network API written in Python. This deep learning Python library can run on top of other source platforms like TensorFlow.
Keras is based on minimizing the delay between the implementation of an idea and the result. The minimization of this delay is the key to good research.
Installing a Python package is generally easy. We just
pip our way through any package like this:
pip install <package>
It is not a viable option in Anaconda to
pip install keras. So, we have to adapt to a better approach. Take a look at the steps below:
Anaconda Prompt and create a new environment. I have named my environment
new_env—type in the command in my Anaconda Prompt terminal:
conda create --name new_env
Make sure you run
Anaconda Promptas Administrator.
Activate the environment, type:
Now, it’s the time to install Keras. Type the following command:
install -c anaconda keras
This will install keras and many other libraries, including numpy, tensorflow, etc. The command will take some time to download and install all the relevant packages.
Make sure you press y–(Yes) when asked to continue.
Since this is a new environment, a few more installations are required; otherwise, a
ModuleNotFoundError could be generated. Many users using Anaconda either work with Spyder or Jupyter Notebook. Therefore, a user is required to run the following commands, one by one:
conda install spyder
conda install jupyter
If any of the packages are still missing, install the library using the following command:
conda install <package> // package could be matplotlib, pandas, etc.
You are done with the installation of Keras in Anaconda – happy coding!
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