LinkedIn open-sources Dagli, a machine learning library for Java

LinkedIn today open-sourced Dagli, a machine learning library for Java (and other JVM languages) that ostensibly makes it easier to write bug-resistant, readable, modifiable, maintainable, and deployable model pipelines without incurring technical debt. While machine learning maturity in the enterprise is generally increasing, the majority of companies (50%) spend between 8 and 90 days deploying a single machine learning model (with 18% taking longer than 90 days), a 2019 survey from Algorithmia found. Most peg the blame on failure to scale, followed by model reproducibility challenges, a lack of executive buy-in, and poor tooling. With Dagli, the model pipeline is defined as a directed acyclic graph, a graph consisting of vertices and edges with each edge directed from one vertex to another for training and inference. The Dagli environment provides pipeline definitions, static typing, near-ubiquitous immutability, and other features preventing the large majority of potential logic errors.