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The Secrets of Machine Learning: Ten Things You Wish You Had Known
  Earlier to be More Effective at Data Analysis

The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis

4 June 2019
Cynthia Rudin
David Carlson
    HAI
ArXivPDFHTML

Papers citing "The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis"

9 / 9 papers shown
Title
Selecting Interpretability Techniques for Healthcare Machine Learning
  models
Selecting Interpretability Techniques for Healthcare Machine Learning models
Daniel Sierra-Botero
Ana Molina-Taborda
Mario S. Valdés-Tresanco
Alejandro Hernández-Arango
Leonardo Espinosa-Leal
Alexander Karpenko
O. Lopez-Acevedo
23
0
0
14 Jun 2024
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms,
  Challenges
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges
Yunpeng Qing
Shunyu Liu
Jie Song
Huiqiong Wang
Mingli Song
XAI
25
1
0
12 Nov 2022
A Survey on Interpretable Reinforcement Learning
A Survey on Interpretable Reinforcement Learning
Claire Glanois
Paul Weng
Matthieu Zimmer
Dong Li
Tianpei Yang
Jianye Hao
Wulong Liu
OffRL
21
91
0
24 Dec 2021
Supervising the Decoder of Variational Autoencoders to Improve
  Scientific Utility
Supervising the Decoder of Variational Autoencoders to Improve Scientific Utility
Liyun Tu
Austin Talbot
Neil Gallagher
David Carlson
DRL
23
2
0
09 Sep 2021
Ten Quick Tips for Deep Learning in Biology
Ten Quick Tips for Deep Learning in Biology
Benjamin D. Lee
A. Gitter
Casey S. Greene
S. Raschka
F. Maguire
...
Alexandr A Kalinin
T. Triche
Benjamin J. Lengerich
Timothy J. Triche Jr
S. Boca
OOD
16
26
0
29 May 2021
Faster SVM Training via Conjugate SMO
Faster SVM Training via Conjugate SMO
Alberto Torres-Barrán
Carlos M. Alaíz
José R. Dorronsoro
14
25
0
19 Mar 2020
Towards CRISP-ML(Q): A Machine Learning Process Model with Quality
  Assurance Methodology
Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology
Stefan Studer
T. Bui
C. Drescher
A. Hanuschkin
Ludwig Winkler
S. Peters
Klaus-Robert Muller
8
173
0
11 Mar 2020
Learning Certifiably Optimal Rule Lists for Categorical Data
Learning Certifiably Optimal Rule Lists for Categorical Data
E. Angelino
Nicholas Larus-Stone
Daniel Alabi
Margo Seltzer
Cynthia Rudin
46
195
0
06 Apr 2017
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,743
0
26 Sep 2016
1