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Tag: sklearn

Towards Predictive Accuracy: Tuning Hyperparameters and Pipelines
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 and complementary Domino project evaluates hyperparameters including GridSearch and RandomizedSearch as well as building an automated ML workflow. Introduction Data scientists, machine learning (ML) researchers, …
How to automate artistic taste (Basic clustering example with python and sklearn)
Cellular automata patterns are clustered based on features related to beauty such as fractal dimensionality and compression efficiency in order to find out the most interesting ones.
Essential Tips and Tricks for Starting Machine Learning with Python
We describe some essential hacks and tricks for practicing machine learning with Python. Covers most important libraries, and the overall approach.
My Thoughts on Synthetic Data
A (relatively) brief introductory analysis on the effectiveness of synthesizing data for machine learning.