"Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases"

entries per page

Filter:

Showing 1 to 20 of 100 entries

Book	Author(s)	Year	Publisher
Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases	Alok Kumar; Mayank Jain	1st ed.	Apress
Ensemble Machine Learning: Methods and Applications	Cha Zhang; Yunqian Ma	2012	Springer New York
Understanding Artificial Intelligence: Fundamentals, Use Cases and Methods for a Corporate AI Journey	Ralf T. Kreutzer; Marie Sirrenberg	1st ed. 2020	Springer International Publishing
Practical AI for Healthcare Professionals: Machine Learning with Numpy, Scikit-learn, and TensorFlow	Abhinav Suri	1st ed.	Apress
Machine Learning for Developers	Rodolfo Bonnin	0	Packt Publishing - ebooks Account
Machine Learning for Developers.	Bonnin, Rodolfo	2017	Packt Publishing
Learn Objective-C for Java Developers	James Bucanek	1st ed.	Apress
Machine Learning for iOS Developers	Abhishek Mishra	2020	John Wiley & Sons
AI for Learning	Carmel Kent; Benedict du Boulay	2022	Routledge
Reinforcement Learning Algorithms with Python: Learn, understand, and develop smart algorithms for addressing AI challenges	Andrea Lonza	2019	Packt Publishing
Methods for Neural Ensemble Recordings	Miguel A. L. Nicolelis	2007	Routledge
Methods for neural ensemble recordings	Miguel A. L. Nicolelis	1998	CRC Press
Machine Learning Projects for. NET Developers	Mathias Brandewinder	1st ed.	Apress
Applied Edge AI: Concepts, Platforms, and Industry Use Cases	Pethuru Raj Chelliah; G. Nagarajan; R.I. Minu	2022	Routledge
Hands-on Ensemble Learning with R	Prabhanjan Narayanachar Tattar	2018	Packt
Hands-On Ensemble Learning with Python	George Kyriakides; Konstantinos G Margaritis	2019	Packt Publishing, Limited
Feature selection and ensemble methods for bioinformatics	Okun O	2011	IGI Global
Natural Language Processing and Machine Learning for Developers	Oswald Campesato	2021	Mercury Learning and Information
Land use guide for builders,developers,and planners	Shepard D. Robinson	1977	Structures Pub. Co.
MACHINE LEARNING WITH PYTORCH AND SCIKIT-LEARN: develop machine learning and deep learning. . . models with scikit-learn and pytorch.	SEBASTIAN LIU YUXI (HAYDEN) MIRJALILI VAHID RASCHKA	2022	PACKT PUBLISHING LIMITED
Boook	Author(s)	Year	Publisher

Showing 1 to 20 of 100 entries

entries per page

Filter:

Showing 1 to 20 of 100 entries

Chapter	Author(s)	Book	Book Authors	Year	Publisher
Bagging, Boosting and Ensemble Methods	Peter Bühlmann	Handbook of Computational Statistics: Concepts and Methods	James E. Gentle; Wolfgang Karl Härdle; Yuichi Mori	2nd ed. 2012. revised and updated	Springer Berlin Heidelberg
Ensemble methods: Bagging and boosting		Machine Learning A First Course for Engineers and Scientists [draft]	Andreas Lindholm, Niklas Wahlström, Fredrik Lindsten, Thomas B. Schön	2021
81 Ensemble techniques: Bagging, boosting, and stacking		Machine Learning with R, Tidyverse, and Mlr	Hefin Ioan Rhys	2020	Manning Publications
621 Bagging, Boosting and Stacking		Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI.	Shlomo Kashani, Amir Ivry (editor)	2020	Interviews AI
631 Bagging, Boosting and Stacking		Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI.	Shlomo Kashani, Amir Ivry (editor)	2020	Interviews AI
10 Ensemble Learning mittels Bagging und Boosting		Maschinelles Lernen - Grundlagen und Algorithmen in Python	Jörg Frochte	2021	Hanser
Ensemble Method Combination: Bagging and Boosting	Jyoti Deshmukh; Mukul Jangid; Shreeshail Gupte; Siddhartha Ghosh; Shubham Ingle	Advanced Computing Technologies and Applications: Proceedings of 2nd International Conference on Advanced Computing Technologies and Applications—ICACTA 2020	Hari Vasudevan; Antonis Michalas; Narendra Shekokar; Meera Narvekar	1st ed. 2020	Springer Nature Singapore
Reranking for Stacking Ensemble Learning	Buzhou Tang; Qingcai Chen; Xuan Wang; Xiaolong Wang	Neural Information Processing. Theory and Algorithms: 17th International Conference, ICONIP 2010, Sydney, Australia, November 21-25, 2010, Proceedings, Part I	Kok Wai Wong; B. Sumudu U. Mendis; Abdesselam Bouzerdoum	2011	Springer Berlin Heidelberg
Bagging and boosting		Mastering Scala machine learning	Kozlov, Alexander	2016	Packt Publishing
Boosting and Bagging		The Hundred-Page Machine Learning Book	Andriy Burkov	2019	Andriy Burkov
Bagging and Boosting		Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams	A. Bifet	2010	IOS Press
Bagging and Boosting		Encyclopedia of Biostatistics	Peter Armitage, Theodore Colton	2005	John Wiley
Application of Bagging, Boosting and Stacking to Intrusion Detection	Iwan Syarif; Ed Zaluska; Adam Prugel-Bennett; Gary Wills	Machine Learning and Data Mining in Pattern Recognition: 8th International Conference, MLDM 2012, Berlin, Germany, July 13-20, 2012, Proceedings	Petra Perner	2013	Springer Berlin Heidelberg
711 Bagging and Other Ensemble Methods		Deep Learning: Adaptive Computation and Machine Learning	Ian Goodfellow and Yoshua Bengio and Aaron Courville	2016	The MIT Press
Ensemble Methods for Boosting Visualization Models	Bruno Baruque; Emilio Corchado; Aitor Mata; Juan M. Corchado	Bio-Inspired Systems: Computational and Ambient Intelligence: 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, June 10-12, 2009. Proceedings, Part I	Joan Cabestany; Francisco Sandoval; Alberto Prieto; Juan Manuel Corchado Rodríguez	2009	Springer Berlin Heidelberg
Use Cases: Data, AI, and Machine Learning		Modernizing Enterprise Java: A Concise Cloud Native Guide for Developers	Markus Eisele, Natale Vinto	2021	O'Reilly Media
Use Cases: Data, AI, and Machine Learning		Modernizing Enterprise Java - A Concise Cloud Native Guide for Developers (true pdf)	Markus Eisele, Natale Vinto	2022	O'Reilly
Positive Use Cases for AI		The Unintended Consequences Of Technology: Solutions, Breakthroughs, And The Restart We Need	Chris Ategeka	2022	John Wiley & Sons
Exercise 1505: Ensemble Learning Using Bagging		The Data Science Workshop	Robert John; Samuel Asare; Andrew Worsley; Thomas Joseph; Anthony So	2020	Packt Publishing, Limited
Exercise 1505: Ensemble Learning Using Bagging		The Data Science Workshop: A New, Interactive Approach to Learning Data Science	Anthony So; Thomas V. Joseph; Robert Thas John; Andrew Worsley; Dr. Samuel Asare	2020	Packt Publishing
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

"Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases" - similar Books and Chapters