Giuseppe Bonaccorso od wielu lat prowadzi projekty dotyczące sztucznej inteligencji. W kręgu jego głównych zainteresowań znajdują się takie techniki jak uczenie maszynowe, uczenie głębokie, uczenie przez wzmacnianie, a także praca z wielkimi zbiorami danych, systemy adaptacyjne inspirowane układami biologicznymi, kryptowaluty i programowanie neurolingwistyczne.
Giuseppe Bonaccorso - ebooki
Tytuły autora: Giuseppe Bonaccorso dostępne w księgarni Helion
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Celem tej książki jest przybliżenie profesjonalistom tajników złożonych algorytmów uczenia maszynowego i zasad ich stosowania w praktyce. Poza praktycznymi informacjami dotyczącymi działania algorytmów i ich wdrożeń znalazły się tu również niezbędne podstawy teoretyczne. Opisano klasyczne modele uczenia nadzorowanego, nienadzorowanego i półnadzorow
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Algorytmy uczenia maszynowego. Zaawansowane techniki implementacji Algorytmy uczenia maszynowego. Zaawansowane techniki implementacji
Niedostępna
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A new second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems, updated to include Python 3.8 and TensorFlow 2.x as well as the latest in new algorithms and techniques.
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Mastering Machine Learning Algorithms. Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work - Second Edition Mastering Machine Learning Algorithms. Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work - Second Edition
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Unsupervised learning is a key required block in both machine learning and deep learning domains. You will explore how to make your models learn, grow, change, and develop by themselves whenever they are exposed to a new set of data. With this book, you will learn the art of unsupervised learning for different real-world challenges.
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Hands-On Unsupervised Learning with Python. Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more Hands-On Unsupervised Learning with Python. Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more
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This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden
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Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python
Giuseppe Bonaccorso, Armando Fandango, Rajalingappaa Shanmugamani
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Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. This book will act as an entry point for anyone who wants to make a career in Machine Learning. It covers algorithms like Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, and Feature engineeri
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Machine Learning Algorithms. Popular algorithms for data science and machine learning - Second Edition Machine Learning Algorithms. Popular algorithms for data science and machine learning - Second Edition
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This book is your guide to quickly get to grips with the most widely used machine learning algorithms. As a data science professional, this book will help you design and train better machine learning models to solve a variety of complex problems, and make the machine learn your requirements.
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Mastering Machine Learning Algorithms. Expert techniques to implement popular machine learning algorithms and fine-tune your models Mastering Machine Learning Algorithms. Expert techniques to implement popular machine learning algorithms and fine-tune your models
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Machine learning explores the study and construction of algorithms that can learn from, and make predictions on, data. This book will act as an entry point for anyone who wants to make a career in the field of Machine Learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naïve Bayes,
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Machine Learning Algorithms. A reference guide to popular algorithms for data science and machine learning Machine Learning Algorithms. A reference guide to popular algorithms for data science and machine learning
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