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Añadir al carritoPaperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Publicado por The Pragmatic Programmers, US, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
EUR 37,12
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Añadir al carritoPaperback. Condición: New. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.In this book, you will:Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods, including tournament and roulette wheels.Learn about heuristics, fitness functions, metrics, and clusters.Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon.What You Need:Code in C++ (= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.
Publicado por The Pragmatic Programmers, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 36,07
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Librería: Goodwill of Greater Milwaukee and Chicago, Racine, WI, Estados Unidos de America
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Publicado por The Pragmatic Programmers, US, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 41,91
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Añadir al carritoPaperback. Condición: New. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.In this book, you will:Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods, including tournament and roulette wheels.Learn about heuristics, fitness functions, metrics, and clusters.Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon.What You Need:Code in C++ (= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 39,25
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Publicado por The Pragmatic Programmers, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 37,45
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days. 726.
EUR 42,21
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 36,06
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Librería: California Books, Miami, FL, Estados Unidos de America
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Librería: Oblivion Books, Seattle, WA, Estados Unidos de America
EUR 9,99
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Añadir al carritopaperback. Condición: Very Good. VG Softcover. Clean text - NO writing, NO highlighting. Very good. Oversized. Clean text -- NO writing, NO highlighting to text.ÂPLEASE NOTE: Domestic US media (standard) US orders ONLY. NO international orders.
Publicado por The Pragmatic Programmers, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Original o primera edición
EUR 56,27
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Añadir al carritoCondición: New. 2019. 1st Edition. Paperback. . . . . .
Publicado por The Pragmatic Programmers Apr 2019, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 50,59
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally.
Publicado por The Pragmatic Programmers, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 69,02
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Añadir al carritoCondición: New. 2019. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: New. pp. 236.
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Añadir al carritoCondición: New. pp. 236.
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 218 pages. 9.50x7.75x0.75 inches. In Stock.
Publicado por The Pragmatic Programmers, US, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
EUR 71,39
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Añadir al carritoPaperback. Condición: New. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.In this book, you will:Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods, including tournament and roulette wheels.Learn about heuristics, fitness functions, metrics, and clusters.Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon.What You Need:Code in C++ (= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.
Publicado por The Pragmatic Programmers, Raleigh, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 43,62
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Añadir al carritoPaperback. Condición: new. Paperback. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems. In this book, you will: Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods, including tournament and roulette wheels.Learn about heuristics, fitness functions, metrics, and clusters. Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon. What You Need: Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Publicado por Pragmatic Bookshelf (edition 1), 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 10,59
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Añadir al carritoPaperback. Condición: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Publicado por The Pragmatic Programmers, US, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 73,25
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: New. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.In this book, you will:Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods, including tournament and roulette wheels.Learn about heuristics, fitness functions, metrics, and clusters.Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon.What You Need:Code in C++ (= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.
Publicado por Pragmatic Programmers, LLC, The, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: TextbookRush, Grandview Heights, OH, Estados Unidos de America
EUR 29,59
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Añadir al carritoCondición: Very Good. Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy.
Librería: HPB-Red, Dallas, TX, Estados Unidos de America
EUR 9,54
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Añadir al carritoPaperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Publicado por The Pragmatic Programmers, Raleigh, 2019
ISBN 10: 168050620X ISBN 13: 9781680506204
Idioma: Inglés
Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America
EUR 41,65
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Añadir al carritoPaperback. Condición: new. Paperback. Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems. In this book, you will: Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods, including tournament and roulette wheels.Learn about heuristics, fitness functions, metrics, and clusters. Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon. What You Need: Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 41,78
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Publicado por Huazhong University of Science and Technology Press
ISBN 10: 7568089789 ISBN 13: 9787568089784
Idioma: Chino
Librería: liu xing, Nanjing, JS, China
EUR 103,66
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Añadir al carritopaperback. Condición: New. Paperback. Pub Date: 2023-01-01 Pages: 252 Language: Chinese Publisher: Huazhong University of Science and Technology Press Self-driving cars. natural language recognition. and content recommendation engines are all inseparable from artificial intelligence and machine learning algorithms. Machine learning algorithms are only valuable when they solve specific problems. This book aims to solve various interesting problems. and teaches readers to write machine learning algorithms in Python. Java.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 55,64
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Añadir al carritoPaperback. Condición: Brand New. 218 pages. 9.50x7.75x0.75 inches. In Stock. This item is printed on demand.