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This is a and seamlessly integrated minimal runtime environment that combines several powerful components for machine learning and data science:

TensorFlow: An open-source software library for machine learning.
Keras: An open-source neural network library.
Jupyter Notebook: A browser-based interactive programming and data science notebook.
Python: The versatile programming language widely used in machine learning and data analysis.
This stack is specially constructed with a focus on CPU optimization, making it ideal for running machine learning and data science workloads on CPU-based systems. It incorporates the Intel MKL (Math Kernel Library) and MKL-DNN (Deep Neural Network) libraries, which are designed to enhance performance and efficiency when working with mathematical and deep learning operations on CPU.

In addition to these core components, the stack also includes a Development preset, providing essential program development and building tools like a C compiler and make. These tools are valuable for customizing and expanding the capabilities of the stack to suit specific requirements.

In summary, this software environment is well-suited for users who prefer CPU-based machine learning and data science tasks. It offers a seamless integration of TensorFlow, Keras, Jupyter Notebook, and Python while optimizing performance on CPU through Intel MKL and MKL-DNN libraries. It also provides development tools for further customization and flexibility.