Cargando…

Real world active learning : applications and strategies for human-in-the-loop machine learning /

Detalles Bibliográficos
Clasificación:	Libro Electrónico
Autor principal:	Cuzzillo, Ted (Autor)
Formato:	Electrónico eBook
Idioma:	Inglés
Publicado:	Sebastopol, CA : O'Reilly Media, [2015]
Edición:	First edition.
Temas:	Machine learning. Human-computer interaction. Data mining. Apprentissage automatique. Exploration de données (Informatique)
Acceso en línea:	Texto completo (Requiere registro previo con correo institucional)

Ejemplares similares

Merkmalskonstruktion für Machine Learning : Prinzipien und Techniken der Datenaufbereitung /
por: Zheng, Alice, et al.
Publicado: (2019)

Feature engineering for machine learning : principles and techniques for data scientists /
por: Zheng, Alice, et al.
Publicado: (2018)

Praxiseinstieg Machine Learning mit Scikit-Learn und TensorFlow : Konzepte, Tools und Techniken für intelligente Systeme /
por: Raschka, Sebastian
Publicado: (2018)

Leveraging multi-CDN at Riot Games /
Publicado: (2017)

Hands-on machine learning with Microsoft Excel 2019 : build complete data analysis flows, from data collection to visualization /
por: Martino, Julio Cesar Rodriguez
Publicado: (2019)

Hands-on machine learning with Microsoft Excel 2019 : build complete data analysis flows, from data collection to visualization /
por: Martino, Julio Cesar Rodriguez
Publicado: (2019)

Scalable machine learning : complex data analysis at scale /
Publicado: (2015)

Next-generation sequencing and sequence data analysis /
por: Ping Chiu, Kuo
Publicado: (2016)

Machine learning and data mining : introduction to principles and algorithms /
por: Kononenko, Igor, 1959-
Publicado: (2007)

R machine learning by example : understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully /
por: Bali, Raghav, et al.
Publicado: (2016)

R deep learning projects : master the techniques to design and develop neural network models in R /
por: Liu, Yuxi, et al.
Publicado: (2018)

Data mining and machine learning applications /
Publicado: (2022)

New Age Analytics
por: Luna, Alvin Albuero De
Publicado: (2020)

Practical machine learning for data analysis using python /
por: Subasi, Abdulhamit
Publicado: (2020)

Practical machine learning for data analysis using python /
por: Subasi, Abdulhamit
Publicado: (2020)

Becoming a data head : how to think, speak, and understand data science, statistics, and machine learning /
por: Gutman, Alex J., et al.
Publicado: (2021)

Becoming a data head : how to think, speak, and understand data science, statistics, and machine learning /
por: Gutman, Alex J., et al.
Publicado: (2021)

Scaling up machine learning : parallel and distributed approaches /
Publicado: (2012)

Meta-analytics : consensus approaches and system patterns for data analysis /
por: Simske, Steven J.
Publicado: (2019)

Data Mining and Machine Learning in Cybersecurity /
por: Dua, Sumeet, et al.
Publicado: (2016)

What every engineer should know about data-driven analytics /
por: Srinivasan, Satish Mahadevan, et al.
Publicado: (2023)

Introduction to statistical and machine learning methods for data science /
por: Reis Pinheiro, Carlos Andre, 1940-
Publicado: (2021)

Machine learning with Pytorch and Sscikit-Learn : develop machine learning and deep learning models with scikit-learn and PyTorch /
por: Raschka, Sebastian
Publicado: (2022)

Machine learning in the cloud with Azure machine learning /
Publicado: (2018)

Authoring machine learning models from scratch /
Publicado: (2021)

Machine learning and data science with Python : a complete beginners guide /
por: Nelson, Abhilash
Publicado: (2019)

Deep learning with Python : learn best practices of deep learning models with PyTorch /
por: Ketkar, Nikhil, et al.
Publicado: (2021)

Deep learning with Python : learn best practices of deep learning models with PyTorch /
por: Ketkar, Nikhil, et al.
Publicado: (2021)

Applied unsupervised learning with R /
por: Malik, Alok, et al.
Publicado: (2019)

The unsupervised learning workshop get started with unsupervised learning and simplify unorganized data to make predictions /
por: Jones, Aaron, et al.
Publicado: (2020)

Data science revealed : with feature engineering, data visualization, pipeline development, and hyperparameter tuning /
por: Nokeri, Tshepo Chris
Publicado: (2021)

Introduction to algorithms for data mining and machine learning /
por: Yang, Xin-She
Publicado: (2019)

Introduction to Pandas for developers : understand the basic workflows and gotchas of crawling, munging and plotting data /
Publicado: (2016)

Introduction to machine learning with Python : a guide for data scientists /
por: Müller, Andreas C., et al.
Publicado: (2017)

Azure masterclass : manage Azure cloud with ARM templates /
Publicado: (2018)

Meta-analytics : consensus approaches and system patterns for data analysis /
por: Simske, Steven J.
Publicado: (2019)

Evaluating machine learning models : a beginner's guide to key concepts and pitfalls /
por: Zheng, Alice
Publicado: (2015)

Basic statistics and regression for machine learning in Python /
Publicado: (2021)

Statistical learning and data science /
Publicado: (2012)

Practical machine learning for data analysis using python /
por: Subasi, Abdulhamit
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_mp5pqd0qpgoikq7jqrfc16vd2j