Skill

distributed-ml-scaling

Provides expert patterns for scaling data processing and machine learning across machines using Dask and Apache Spark based on Scaling Python with Dask (Karau & Kimmins) and Scaling Machine Learning with Spark (Polak). Covers Dask collections and schedulers, task graphs and lazy execution, Dask-ML, Spark architecture and DataFrames, the MLlib/ML pipeline API, distributed deep-learning bridges (Petastorm, Horovod, TensorFlow/PyTorch strategies), data vs model parallelism, deployment and drift monitoring.

Bundled with Coacus. Its trust score, security findings and other files are on the plugin page.

npx [email protected] add dandgabr/Coacus