98 Interpretable Machine Learning With Serg Masis
98 Interpretable Machine Learning With Serg Masis Youtube One of the biggest challenges facing the adoption of machine learning and ai in data science is understanding, interpreting, and explaining models and their. Serg masis is a climate & agronomic data scientist at syngenta and the author of the book, interpretable machine learning with python. for the last two decades, serg has been at the confluence of the internet, application development, and analytics. serg is a true polymath.
Interpretable Machine Learning With Python Build Explainable Fair Serg masis is a climate & agronomic data scientist at syngenta and the author of the book, interpretable machine learning with python. for the last two decades, serg has been at the confluence of the internet, application development, and analytics. serg is a true polymath. Interpretable machine learning with python. this book dives deep into the essence of making complex machine learning models understandable and accountable. this book covers everything from white box models like linear regression and decision trees to a comprehensive suite of model agnostic methods for black box models. Interpretable machine learning with python can help you overcome these challenges, using interpretation methods to build fairer and safer ml models. this book covers the following exciting features: recognize the importance of interpretability in business; study models that are intrinsically interpretable such as linear models, decision trees. Serg masis is a climate & agronomic data scientist at syngenta and the author of the book, interpretable machine learning with python.serg has developed his expertise in interpretable machine learning, explainable ai, behavioral economics, causal inference, and responsible ethical ai throughout his career, which spans web and software development, mobile app development, systems analyst, ml.
Interpretable Machine Learning With Python By Serg Masís Buy Online In Interpretable machine learning with python can help you overcome these challenges, using interpretation methods to build fairer and safer ml models. this book covers the following exciting features: recognize the importance of interpretability in business; study models that are intrinsically interpretable such as linear models, decision trees. Serg masis is a climate & agronomic data scientist at syngenta and the author of the book, interpretable machine learning with python.serg has developed his expertise in interpretable machine learning, explainable ai, behavioral economics, causal inference, and responsible ethical ai throughout his career, which spans web and software development, mobile app development, systems analyst, ml. Title: interpretable machine learning with python second edition. author (s): serg masís. release date: october 2023. publisher (s): packt publishing. isbn: 9781803235424. a deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including shap, feature importance, and causal. In this episode, serg details what interpretable machine learning is, the key interpretable ml approaches we have today and when they're useful, the social and financial ramifications of getting model interpretation wrong, what agronomy is and how it's increasingly integral to being able to feed the growing population on our warming planet.
Serg Masís Interpretable Machine Learning Data Scientist At Title: interpretable machine learning with python second edition. author (s): serg masís. release date: october 2023. publisher (s): packt publishing. isbn: 9781803235424. a deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including shap, feature importance, and causal. In this episode, serg details what interpretable machine learning is, the key interpretable ml approaches we have today and when they're useful, the social and financial ramifications of getting model interpretation wrong, what agronomy is and how it's increasingly integral to being able to feed the growing population on our warming planet.
Serg Masis Interpretable Machine Learning With Python Youtube
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