From the course: Full-Stack Deep Learning with Python
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Introducing MLflow - Python Tutorial
From the course: Full-Stack Deep Learning with Python
Introducing MLflow
- [Instructor] Now if you were to set up an MLOps workflow for your deep learning system, there are many different tools and technologies that you could use. In this course, however, we'll focus on one, MLflow. MLflow is an open source platform that allows you to manage the entire machine learning lifecycle. MLflow is explicitly designed to simplify and streamline the end-to-end process of developing, training, tuning, and deploying machine learning models. MLflow is designed to be language-agnostic, meaning you can use it with different programming languages and machine learning frameworks. It supports popular languages such as Python and R, as well as machine learning frameworks, such as TensorFlow, PyTorch, and scikit-learn. Let's discuss the components that make up MLflow before we get hands on. MLflow has features that enable tracking of machine learning experiments and runs. MLflow allows you to deal with model…
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