Machine learning algorithms : popular algorithms for data science and machine learning

Machine learning algorithms : popular algorithms for data science and machine learning

Enregistré dans:

Détails bibliographiques
Auteur principal:	Bonaccorso, Giuseppe. (Auteur)
Support:	E-Book
Langue:	Anglais
Publié:	Birmingham : Packt Publishing, 2018.
Autres localisations:	Voir dans le Sudoc
Accès en ligne:	Accès à l'E-book

Documents similaires

Machine Learning Algorithms : Reference guide for popular algorithms for data science and machine learning
par: Bonaccorso, Bonaccorso.
Publié: (2017)

Mastering machine learning algorithms : expert techniques to implement popular machine learning algorithms and fine-tune your models
par: Bonaccorso, Giuseppe.
Publié: (2018)

Mastering machine learning algorithms : expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work
par: Bonaccorso, Giuseppe.
Publié: (2020)

Introduction to Algorithms for Data Mining and Machine Learning
par: Yang, Xin-She (19..-....).
Publié: (2019)

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

Machine Learning and Deep Learning Algorithms : Tools and Techniques Using MATLAB and Python
par: Kumar Pandey, Abhishek.

Genetic algorithms in search, optimization, and machine learning
par: Goldberg, David Edward, 1953-
Publié: (1989)

Advanced Machine Learning : Fundamentals and algorithms
par: Kumar Tyagi, Amit (19..-....).

Machine Learning for Algorithmic Trading : Predictive models to extract signals from market and alternative data for systematic trading strategies with Python
par: Jansen, Stefan.
Publié: (2020)

Graph Machine Learning : Take graph data to the next level by applying machine learning techniques and algorithms
par: Stamile, Claudio (19..-....; chercheur en informatique).
Publié: (2021)

Machine Learning for Biometrics : Concepts, Algorithms and Applications
par: Sarangi, Partha Pratim (19..-....).
Publié: (2022)

Machine Learning : Master Supervised and Unsupervised Learning Algorithms with Real Examples
par: Doshi, Ruchi.

Hands-on unsupervised learning with Python : implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more
par: Bonaccorso, Giuseppe.
Publié: (2019)

Machine Learning with Scala Quick Start Guide : Leverage popular machine learning algorithms and techniques and implement them in Scala
par: Karim, Rezaul Md..
Publié: (2019)

Hands-On Machine Learning with ML.NET : Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
par: Capellman, Jarred.
Publié: (2020)

Learning genetic algorithms with Python : empower the performance of machine learning and AI models with the capabilities of a powerful search algorithm
par: Gridin, Ivan.

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

MATLAB for machine learning
par: Ciaburro, Giuseppe (19..-....).
Publié: (2017)

Machine Learning for finance : The practical guide to using data-driven algorithms in banking, insurance, and investments
par: Klaas, Jannes.
Publié: (2019)

Learning functional data structures and algorithms
par: Khot, Atul S..
Publié: (2017)

Data science algorithms in a week : top 7 algorithms for scientific computing, data analysis, and machine learning
par: Natingga, David.
Publié: (2018)

Algorithmes et machines à calculer
par: Trahtenbrot, Boris Avraamovich.
Publié: (1963)

Hands-On Machine Learning with IBM Watson : Leverage IBM Watson to Implement Machine Learning Techniques and Algorithms Using Python
par: Miller, James D..
Publié: (2019)

Learn Algorithmic Trading : Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis
par: Donadio, Sebastien.
Publié: (2019)

Learning F# functional data structures and algorithms
par: Masood, Adnan.
Publié: (2015)

Learning JavaScript data structures and algorithms
par: Groner, Loiane.
Publié: (2014)

Learning JavaScript data structures and algorithms
par: Groner, Loiane.
Publié: (2016)

Machine learning for cybersecurity cookbook : over 80 recipes on how to implement machine learning algorithms for building security systems using Python
par: Tsukerman, Emmanuel.
Publié: (2019)

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

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

Reinforcement Learning Algorithms with Python : Learn, understand, and develop smart algorithms for addressing AI challenges
par: Lonza, Andrea.
Publié: (2019)

Automated Machine Learning : Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms
par: Masood, Adnan.
Publié: (2021)

Machine Learning for Imbalanced Data : Tackle imbalanced datasets using machine learning and deep learning techniques
par: Abhishek, Kumar.

Data Science with Machine Learning : Python Interview Questions
par: Narayanan, Vishwanathan.

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
par: Bali, Raghav (19..-....).
Publié: (2016)

Python : expert machine learning systems and intelligent agents using Python
par: Bonaccorso, Giuseppe.
Publié: (2018)

Machine Learning with R : Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data
par: Lantz, Brett.

Synthetic Data for Machine Learning : Revolutionize your approach to machine learning with this comprehensive conceptual guide
par: Kerim, Abdulrahman.

Mastering machine learning with scikit-learn : learning to implement and evaluate machine learning solutions with scikit-learn
par: Hackeling, Gavin.
Publié: (2017)

Python machine learning cookbook : over 100 recipes to progress from smart data analytics to deep learning using real-world datasets
par: Ciaburro, Giuseppe (19..-....).
Publié: (2019)

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