Subject archive for "python," page 7

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Fenner. The excerpt evaluates hyperparameters including GridSearch and RandomizedSearch as well as building an automated ML workflow.

This blog post provides insights on how to use the SHAP and LIME Python libraries in practice and how to interpret their output, helping readers prepare to produce model explanations in their own work. If interested in a visual walk-through of this post, then consider attending the webinar.

In this guest post, Holden Karau, Apache Spark Committer, provides insights on how to create multi-language pipelines with Apache Spark and avoid rewriting spaCy into Java. She has already written a complementary blog post on using spaCy to process text data for Domino. Karau is a Developer Advocate at Google as well as a co-author on High Performance Spark and Learning Spark. She also has a repository of her talks, code reviews, and code sessions on Twitch and Youtube.

Paco Nathan's latest column covers themes that include data privacy, machine ethics, and yes, Don Quixote.

This blog post provides a brief technical introduction to the SHAP and LIME Python libraries, followed by code and output to highlight a few pros and cons of each. If interested in a visual walk-through of this post, consider attending the webinar.

In this guest post, Holden Karau, Apache Spark Committer, provides insights on how to use spaCy to process text data. Karau is a Developer Advocate at Google, as well as a co-author of "High Performance Spark" and "Learning Spark". She has a repository of her talks, code reviews and code sessions on Twitch and YouTube. She is also working on Distributed Computing 4 Kids.