Projects: pypi: keras-vis
https://packages.ecosyste.ms/registries/pypi.org/packages/keras-vis
Neural Network visualization toolkit for keras
11 versions
Latest release: about 9 years ago
908 downloads last month
Enhanced Analysis
Repository Activity:
Repository Owner:
Raghavendra Kotikalapudi (user)
Learning to machine learn
Learning to machine learn
README Analysis:
Science Score: 75/100
Starting Score: 100 points
Bonuses:
-
+10
Science terms in README
5 scientific terms found in README
Penalties:
-
-10
PyPI ecosystem
General-purpose ecosystem -
-15
No science keywords
No scientific terms found in keywords/classifiers
Very Likely Science (75)
Papers Mentioning keras-vis 6
10.7554/eLife.64669
Detecting adaptive introgression in human evolution using convolutional neural networksCited by: 52
Author(s): Graham Gower, Pablo Iáñez Picazo, Matteo Fumagalli, Fernando Racimo
Software Mentions: 5
Published: about 5 years ago
10.1038/s41598-021-87557-5
Efficient few-shot machine learning for classification of EBSD patternsCited by: 15
Author(s): Kevin Kaufmann, Hobson Lane, Xiao Liu, Kenneth S. Vecchio
Software Mentions: 3
Published: over 5 years ago
10.1186/s12916-020-01684-w
Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networksCited by: 28
Author(s): Kun‐Hsing Yu, Vincent J. Hu, Feiran Wang, Ursula A. Matulonis, George L. Mutter, Jeffrey A. Golden, Isaac S. Kohane
Software Mentions: 2
Published: about 6 years ago
10.1186/s12920-020-0677-2
Convolutional neural network models for cancer type prediction based on gene expressionCited by: 84
Author(s): Milad Mostavi, Yi-Chang Chiu, Yufei Huang, Yidong Chen
Software Mentions: 2
Published: over 6 years ago
10.3390/molecules24112097
A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRsCited by: 29
Author(s): Ambrose Plante, Derek M. Shore, Giulia Morra, George Khelashvili, Harel Weinstein
Software Mentions: 2
Published: about 7 years ago
10.1371/journal.pone.0217075
Distillation of crop models to learn plant physiology theories using machine learningCited by: 5
Author(s): Kyosuke Yamamoto
Software Mentions: 1
Published: about 7 years ago