Mastering machine learning with scikit-learn : learning to implement and evaluate machine learning solutions with scikit-learn

Mastering machine learning with scikit-learn : learning to implement and evaluate machine learning solutions with scikit-learn

Guardat en:

Dades bibliogràfiques
Autor principal:	Hackeling, Gavin. (Autor)
Format:	E-Book
Idioma:	Anglais
Publicat:	Birmingham, UK : Packt Publishing Ltd, 2017.
Matèries:	Machine learning.
Autres localisations:	Voir dans le Sudoc
Accés en línia:	Accès à l'E-book

Ítems similars

Machine learning : theory and applications
per: Govindaraju, Venugopal (1964-....).
Publicat: (2013)

Dataset Shift in Machine Learning
per: Joaquin, Quiñonero-Candela.

Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications
per: Lantz, Brett.
Publicat: (2013)

An introduction to computational learning theory
per: Kearns, Michael J..
Publicat: (1994)

Mastering .NET machine learning : master the art of machine learning with .NET and gain insight into real-world applications
per: Dixon, Jamie.
Publicat: (2016)

Machine learning avec Scikit-Learn : mise en oeuvre et cas concrets
per: Géron, Aurélien (19..-....).

Scikit-learn : machine learning simplified
per: Garreta, Raúl.
Publicat: (2017)

Python machine learning
per: Lee, Wei-Meng (19..-....).

Large-Scale Kernel Machines
per: Bottou, Léon (1965-....).

Machine learning for developers : uplift your regular applications with the power of statistics, analytics, and machine learning
per: Bonnin, Rodolfo.
Publicat: (2017)

Building Machine Learning Systems with Python : master the art of machine learning with Python and build effective machine learning systems with this intensive hands-on guide
per: Richert, Willi.
Publicat: (2013)

Practical machine learning in R
per: Nwanganga, Fred (19..-....).

Machine Learning with PyTorch and Scikit-Learn : Develop machine learning and deep learning models with Python
per: Raschka, Sebastian.
Publicat: (2022)

F# for machine learning essentials : get up and running with machine learning with F# in a fun and functional way
per: Mukherjee, Sudipta.
Publicat: (2016)

Machine learning for planetary science
per: Helbert, Joern.
Publicat: (2022)

Evolution and Learning The Baldwin Effect Reconsidered
per: Weber, Bruce H..

Machine learning : a bayesian and optimization perspective
per: Theodoridis, Sergios.
Publicat: (2015)

Optimization for machine learning
per: Sra, Suvrit (1976-....).
Publicat: (2011)

Invertebrate learning and memory
per: Menzel, Randolf (1940-....).
Publicat: (2013)

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits : A practical guide to implementing supervised and unsupervised machine learning algorithms in Python
per: Amr, Tarek (19..-....).
Publicat: (2020)

Scikit-learn cookbook
per: Avila, Julian (19..-....).
Publicat: (2017)

Gaussian Processes for Machine Learning
per: Rasmussen, Carl Edward (1969-....).
Publicat: (2005)

Machine learning with scikit-learn quick start guide : classification, regression, and clustering techniques in Python
per: Jolly, Kevin.
Publicat: (2018)

Machine learning
per: Mueller, John Paul (1958-....).

Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python
per: Raschka, Sebastian.
Publicat: (2016)

Mastering predictive analytics with scikit-learn and TensorFlow : implement machine learning techniques to build advanced predictive models using Python
per: Fontaine, Alan.
Publicat: (2018)

Statistical and Machine Learning Approaches for Network Analysis
per: Dehmer, Matthias (1968-....).
Publicat: (2012)

Introduction to statistical machine learning
per: Sugiyama, Masashi.
Publicat: (2015)

Python Machine Learning : Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
per: Raschka, Sebastian.
Publicat: (2019)

Changing Minds Computers, Learning, and Literacy
per: DiSessa, Andrea A. (1947-....).

Beginning with Machine Learning : The Ultimate Introduction to Machine Learning, Deep Learning, Scikit-learn, and TensorFlow (English Edition)
per: Dua, Amit.

Deep learning with Keras : implement neural networks with Keras on Theano and TensorFlow
per: Gulli, Antonio.
Publicat: (2017)

Machine learning fundamentals : use Python and scikit-learn to get up and running with the hottest developments in machine learning
per: Saleh, Hyatt.
Publicat: (2018)

The machine learning workshop : get ready to develop your own high-performance machine learning algorithms with scikit-learn
per: Saleh, Hyatt.
Publicat: (2020)

Hands-On Gradient Boosting with XGBoost and scikit-learn : Perform accessible machine learning and extreme gradient boosting with Python
per: Wade, Corey.
Publicat: (2020)

Learning Bayesian models with R : become an expert in Bayesian machine learning methods using R and apply them to solve real-world big data problems
per: Koduvely, Hari M..
Publicat: (2015)

Machine-to-machine (M2M) communications : architecture, performance and applications
Publicat: (2014)

Mastering Classification Algorithms for Machine Learning : Learn how to apply Classification algorithms for effective Machine Learning solutions
per: Majumdar, Partha.

Mastering Java machine learning
per: Kamath, Dr. Uday.
Publicat: (2017)

Mastering machine learning with R
per: Lesmeister, Cory.
Publicat: (2017)

Université catholique de l'Ouest - Bibliothèques - 3 place André Leroy - BP10808 - 49008 ANGERS Cedex 1