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MLflow 1.6.0

@AveshCSingh AveshCSingh released this
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1.6.0 (2020-01-29)

MLflow 1.6.0 includes several new features, including a better runs table interface, a utility for easier parameter tuning, and automatic logging from XGBoost, LightGBM, and Spark. It also implements a long-awaited fix allowing @ symbols in database URLs. A complete list is below:

Features:

  • Adds a new runs table column view based on ag-grid which adds functionality for nested runs, serverside sorting, column reordering, highlighting, and more. (#2251, @Zangr)
  • Adds contour plot to the run comparsion page to better support parameter tuning (#2225, @harupy)
  • If you use EarlyStopping with Keras autologging, MLflow now automatically captures the best model trained and the associated metrics (#2301, #2219, @juntai-zheng)
  • Adds autologging functionality for LightGBM and XGBoost flavors to log feature importance, metrics per iteration, the trained model, and more. (#2275, #2238, @harupy)
  • Adds an experimental mlflow.spark.autolog() API for automatic logging of Spark datasource information to the current active run. (#2220, @smurching)
  • Optimizes the file store to load less data from disk for each operation (#2339, @jonas)
  • Upgrades from ubuntu:16.04 to ubuntu:18.04 when building a Docker image with mlflow models build-docker (#2256, @andychow-db)

Bug fixes and documentation updates:

Small bug fixes and doc updates (#2293, #2328, #2244, @harupy; #2269, #2332, #2306, #2307, #2292, #2267, #2191, #2231, @juntai-zheng; #2325, @shubham769; #2291, @sueann; #2315, #2249, #2288, #2278, #2253, #2181, @smurching; #2342, @tomasatdatabricks; #2245, @dependabot[bot]; #2338, @jcuquemelle; #2285, @avflor; #2340, @pogil; #2237, #2226, #2243, #2272, #2286, @dbczumar; #2281, @renaudhager; #2246, @avaucher; #2258, @lorenzwalthert; #2261, @smith-kyle; 2352, @dbczumar)