Machine Learning Workbench, offered by Elm Computing, is a pre-configured environment designed to streamline the development and deployment of machine learning models. Built upon a JupyterHub server, it comes equipped with popular Python packages such as TensorFlow and PyTorch, facilitating efficient collaboration among single or multiple users. This workbench simplifies the setup process, allowing data scientists and developers to focus on model development without the overhead of configuring their environment. Key Features and Functionality: - Pre-Configured Environment: Includes essential machine learning libraries like TensorFlow and PyTorch, reducing setup time. - JupyterHub Integration: Supports collaborative development through a shared Jupyter notebook interface. - Multi-User Support: Designed to serve Jupyter notebooks efficiently for both single and multiple users. - Maintenance Support: Offers additional support services provided by Elm Computing. Primary Value and Problem Solved: Machine Learning Workbench addresses the common challenges of setting up and maintaining a robust machine learning environment. By providing a ready-to-use platform with essential tools and libraries pre-installed, it enables users to focus on developing and deploying models, thereby accelerating the machine learning lifecycle and enhancing productivity.