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In den WarenkorbZustand: New. KlappentextIn Part I of this series, we cover basic statistical inference and experimentation, focusing on: basic statisticsderivation and review of key distributions and their relationshypothesis testi.
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Sprache: Englisch
Verlag: Cayenne Canyon Press Apr 2021, 2021
ISBN 10: 1941043119 ISBN 13: 9781941043110
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Taschenbuch. Zustand: Neu. Neuware - In Part I of this series, we cover basic statistical inference and experimentation, focusing on:
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 314 | Sprache: Englisch | Produktart: Bücher | In Part I of this series, we cover basic statistical inference and experimentation, focusing on: basic statistics;derivation and review of key distributions and their relations;hypothesis testing, including an in depth power analysis for the chi-squared statistic;experimentation, including A/B tests, stratification, one- and two-factor experiments, and an introduction to bandit algorithms; maximum likelihood;gradient descent;introduction to survival analysis and stochastic processes, including empirical estimation of online survival and event processes.The theory is illustrated with simulations in Python throughout the text.
Zustand: Gut. Zustand: Gut | Seiten: 316 | Sprache: Englisch | Produktart: Bücher | In Part III of this series, we cover the fundamentals of machine learning, focusing on:validation methodology (reprint)nearest neighbor, k-means, support vector machines, principal component analysistree-based methods: decision trees, bagging, random forest, boosting, XGBoostartificial neural networks and deep learningreinforcement learningThe focus is on algorithmic development and programming. We code each technique from scratch in Python, using an object-oriented approach.
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 316 | Sprache: Englisch | Produktart: Bücher | In Part III of this series, we cover the fundamentals of machine learning, focusing on:validation methodology (reprint)nearest neighbor, k-means, support vector machines, principal component analysistree-based methods: decision trees, bagging, random forest, boosting, XGBoostartificial neural networks and deep learningreinforcement learningThe focus is on algorithmic development and programming. We code each technique from scratch in Python, using an object-oriented approach.
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 722 | Sprache: Englisch | Produktart: Bücher | Learn Calculus, the easy way! This volume covers both differential and integral calculus, focusinging on conept, technique, and application:concept: a fresh perspective on the key concepts explained step-by-step in a way that students can understandtechnique: a few simple rules is all you need! A Calculus is a simple method for calculating, yet most other texts make it hopelessly confusing. It's actually meant to be easy. We state the key rules clearly and simply, do some examples, and carry on from there. application: this goes beyond any other text to prepare students for advanced courses in mathematics, science, and engineering. This book teaches the art of problem solving, covering a diverse range of interesting real-world applications.This text can be used as a two-semester applied calculus course for engineers, physicisits, and other students of the mathematical sciences. Be sure to check out our page Discovering Calculus on YouTube for free Calculus lectures and worked examples from the author. [LINK ENTFERNT].