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hyperparameter-tuning

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automl / auto-sklearn

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Example fails while building doc

eddiebergman
eddiebergman commented Jul 29, 2021

Building the doc fails for example 40_advanced/example_single_configurations on the current development branch

Logs here

...
generating gallery for examples/40_advanced... [ 50%] example_debug_logging.py

Warning, treated as error:
/home/runner/work/auto-sklearn/auto-sklearn/examples/40_advanced/example_single_configu
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bug Good first issue
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LiYangHart / Hyperparameter-Optimization-of-Machine-Learning-Algorithms

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Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

machine-learning deep-learning random-forest optimization svm genetic-algorithm machine-learning-algorithms hyperparameter-optimization artificial-neural-networks grid-search tuning-parameters knn bayesian-optimization hyperparameter-tuning random-search particle-swarm-optimization hpo python-examples python-samples hyperband
  • Updated Aug 19, 2021
  • Jupyter Notebook

amanchadha / coursera-deep-learning-specialization

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Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

deep-learning neural-network coursera recurrent-neural-networks neural-networks hyperparameter-optimization regularization convolutional-neural-networks neural-machine-translation coursera-machine-learning convolutional-neural-network hyperparameter-tuning andrew-ng coursera-assignment cnns rnns andrew-ng-course recurrent-neural-network neural-style-transfer coursera-specialization
  • Updated Aug 22, 2021
  • Jupyter Notebook
Neuraxle

Neuraxio / Neuraxle

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Code Style: Improve Code Style

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guillaume-chevalier
guillaume-chevalier commented Jun 28, 2021

Describe the bug
Code could be more conform to pep8 and so forth.

To Reproduce
https://app.codacy.com/gh/Neuraxio/Neuraxle/issues?&filters=W3siaWQiOiJMYW5ndWFnZSIsInZhbHVlcyI6W119LHsiaWQiOiJDYXRlZ29yeSIsInZhbHVlcyI6WyJDb2RlU3R5bGUiXX0seyJpZCI6IkxldmVsIiwidmFsdWVzIjpbXX0seyJpZCI6IlBhdHRlcm4iLCJ2YWx1ZXMiOltdfSx7ImlkIjoiQXV0aG9yIiwidmFsdWVzIjpbXX1d

Expected behavior
Less code st

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good first issue invalid documentation
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evalml

alteryx / evalml

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Modify our code to initialize woodwork with partial schemas

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freddyaboulton
freddyaboulton commented Sep 3, 2021

Woodwork introduced the ability to initialize typing information with a partial schema in alteryx/woodwork#1100

This means that we can potentially get rid of _retain_custom_types_and_intialize_woodwork and therefore retain more than just the logical types after some components modify the input data in a way that breaks the woodwork schema.

For example, this is how t

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refactor good first issue
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