Subject archive for "practical-techniques," page 6

This article provides an excerpt "Deep Reinforcement Learning" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. It also covers using Keras to construct a deep Q-learning network that learns within a simulated video game environment. Many thanks to Addison-Wesley Professional for the permission to excerpt the chapter.

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.

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt "Natural Language Processing" from the book, Deep Learning Illustrated by Krohn, Beyleveld, and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

Many thanks to AWP Pearson for the permission to excerpt "Manual Feature Engineering: Manipulating Data for Fun and Profit" from the book, Machine Learning with Python for Everyone by Mark E. Fenner.

Joshua Poduska provides a distilled overview of Ludwig including when to use Ludwig’s command-line syntax and when to use its Python API.

Paco Nathan's latest article covers program synthesis, AutoPandas, model-driven data queries, and more.