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Explainable Machine Learning with LIME and H2O in R(으)로 돌아가기

Coursera Project Network의 Explainable Machine Learning with LIME and H2O in R 학습자 리뷰 및 피드백

54개의 평가

강좌 소개

Welcome to this hands-on, guided introduction to Explainable Machine Learning with LIME and H2O in R. By the end of this project, you will be able to use the LIME and H2O packages in R for automatic and interpretable machine learning, build classification models quickly with H2O AutoML and explain and interpret model predictions using LIME. Machine learning (ML) models such as Random Forests, Gradient Boosted Machines, Neural Networks, Stacked Ensembles, etc., are often considered black boxes. However, they are more accurate for predicting non-linear phenomena due to their flexibility. Experts agree that higher accuracy often comes at the price of interpretability, which is critical to business adoption, trust, regulatory oversight (e.g., GDPR, Right to Explanation, etc.). As more industries from healthcare to banking are adopting ML models, their predictions are being used to justify the cost of healthcare and for loan approvals or denials. For regulated industries that use machine learning, interpretability is a requirement. As Finale Doshi-Velez and Been Kim put it, interpretability is "The ability to explain or to present in understandable terms to a human.". To successfully complete the project, we recommend that you have prior experience with programming in R, basic machine learning theory, and have trained ML models in R. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰


2020년 8월 5일

A Nice choice of the contents in this course, I must say! A good guided that I should recommend everyone to take. Good luck!


2020년 7월 15일

It was an interesting course, explaining hat is happening inside a machine learning algorithm.

필터링 기준:

Explainable Machine Learning with LIME and H2O in R의 9개 리뷰 중 1~9

교육 기관: Khandaker M A

2020년 8월 6일

교육 기관: Lasai B T

2020년 11월 24일

교육 기관: Maria S

2020년 7월 16일

교육 기관: Cheikh B

2020년 11월 19일

교육 기관: H. D S

2021년 8월 10일

교육 기관: Chow K M

2022년 3월 6일

교육 기관: Kadek A W

2020년 7월 8일

교육 기관: ARAVIND K R

2020년 7월 7일

교육 기관: Simon S R

2020년 9월 2일