Training Deep Learning Models using Prefect

Prefect

Prefect is an open-source workflow management system that allows you to build, schedule, and monitor data workflows. It enables you to transform any Python function into a unit of work that can be observed and orchestrated. Prefect can be used for various use cases such as ETL pipelines, machine learning workflows, data warehousing, and more. It has a dynamic engine and ephemeral API that makes it easy to run workflows interactively during the building phase. Prefect also offers the ability to cache and persist inputs and outputs for large files and expensive operations, improving development time when debugging.

Deep Learning Models

Deep learning (DL) is a subset of machine learning that uses neural networks with three or more layers to simulate the behavior of the human brain. Deep learning models are popular because they can learn from large amounts of data and perform tasks that would normally require human intelligence to complete. Deep learning models include convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory networks (LSTMs), restricted Boltzmann machines (RBMs), autoencoders, generative adversarial networks (GANs), residual neural networks (ResNets), self-organizing maps (SOMs), deep belief networks (DBNs), and multilayer perceptrons (MLPs).

Open source orchestrators like Prefect are one of the primary means by which companies train deep learning models in production. Prefect offers a mechanism to schedule and monitor these jobs as part of more complex workflow graphs. Kaspian has a native operator for Prefect; this operator makes it easy to either swap to or get started with training pipelines that utilize Kaspian's flexible compute layer, with native support for autoscaling, GPU acceleration, and more.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.