SKIL Documentation

Skymind Intelligence Layer

The community edition of the Skymind Intelligence Layer (SKIL) is free. It takes data science projects from prototype to production quickly and easily. SKIL bridges the gap between the Python ecosystem and the JVM with a cross-team platform for Data Scientists, Data Engineers, and DevOps/IT. It is an automation tool for machine-learning workflows that enables easy training on Spark-GPU clusters, experiment tracking, one-click deployment of trained models, model performance monitoring and more.

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System Overview

SKIL bridges the gap between data scientists and deployment (devops) engineers by providing all of the necessary tools to build, train, and deploy a model.

Workflow

Because deploying a model requires input from more than just data scientists, SKIL has a collaborative UI and extensive Command Line (CLI) to help devops engineers and product managers participate in fine-tuning and serving models at scale. SKIL reduces friction between all parties in the data science workflow and helps you scale your model faster.

Teams using SKIL can expect support for the following workflows:

  • Model and data configuration
  • DNN Training
  • Collaborative user interfaces for data and results
  • Versioning of experiments and models
  • Scalable microservice deployment architecture
  • APIs for model serving
  • Management UI

To learn more and get started with the SKIL workflow, read the Workflow Overview.

Architecture

Using well-known tools for data science and distributed systems, SKIL is built on the JVM and uses several bindings to unite common deep learning frameworks and distributed storage systems.

Deep Learning Frameworks

Users of SKIL can expect support for TensorFlow, Keras, and Deeplearning4j. All Keras backends are supported or any other models that use Keras 2.0 weight ordering.

Distributed Computing

SKIL is compatible with the Apache Spark and Hadoop ecosystem, allowing for more complex storage of data and operations such as Batch Inference.

Microservices

SKIL itself is accessible as a microservice in your architecture, and exposes key APIs for serving models and transforming data. See our API Reference.