Isbn: 9781617295355 - math for programmers: 3d graphics, machine learning, and simulations with python (23 risultati)

Condizione: very_good.

Condizione: good. Paperback Book.

Paperback. Condizione: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condizione: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condizione: Fair. To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer.   Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting?and lucrative!?careers in some of today?s hottest programming fields.   Key Features ·   2D and 3D vector math ·   Matrices and linear transformations ·   Core concepts from linear algebra ·   Calculus with one or more variables ·   Algorithms for regression, classification, and clustering ·   Interesting real-world examples   Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required.   About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis.   Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington.…

Paperback. Condizione: 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.

Paperback. Condizione: Fair. To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer.   Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting?and lucrative!?careers in some of today?s hottest programming fields.   Key Features ·   2D and 3D vector math ·   Matrices and linear transformations ·   Core concepts from linear algebra ·   Calculus with one or more variables ·   Algorithms for regression, classification, and clustering ·   Interesting real-world examples   Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required.   About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis.   Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington.…

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Paperback. Condizione: new. New Copy. Customer Service Guaranteed.

Paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: new. Paperback. To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interestingand lucrative!careers in some of todays hottest programming fields. Key Features 2D and 3D vector math Matrices and linear transformations Core concepts from linear algebra Calculus with one or more variables Algorithms for regression, classification, and clustering Interesting real-world examples Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required. About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis. Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: New. 2021. 1st Edition. Paperback. . . . . .

Paperback. Condizione: New. To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer.   Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting-and lucrative!-careers in some of today's hottest programming fields.   Key Features ·   2D and 3D vector math ·   Matrices and linear transformations ·   Core concepts from linear algebra ·   Calculus with one or more variables ·   Algorithms for regression, classification, and clustering ·   Interesting real-world examples   Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required.   About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis.   Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington.…

Condizione: New. In English.

Paperback. Condizione: Brand New. 655 pages. 9.25x7.25x1.25 inches. In Stock.

Condizione: New. 2021. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Condizione: New. &Uumlber den AutorPaul Orland&nbspis CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to prod.

Taschenbuch. Condizione: Neu. Neuware - To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting?and lucrative!?careers in some of today's hottest programming fields. Key Features 2D and 3D vector math Matrices and linear transformations Core concepts from linear algebra Calculus with one or more variables Algorithms for regression, classification, and clustering Interesting real-world examples Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required. About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis. Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington.…

Paperback. Condizione: Brand New. 655 pages. 9.25x7.25x1.25 inches. In Stock.

Paperback. Condizione: New. To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer.   Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting-and lucrative!-careers in some of today's hottest programming fields.   Key Features ·   2D and 3D vector math ·   Matrices and linear transformations ·   Core concepts from linear algebra ·   Calculus with one or more variables ·   Algorithms for regression, classification, and clustering ·   Interesting real-world examples   Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required.   About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis.   Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington.…

Taschenbuch. Condizione: Neu. Math for Programmers | Paul Orland | Taschenbuch | Kartoniert / Broschiert | Englisch | 2021 | Manning Publications | EAN 9781617295355 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Paperback. Condizione: new. Paperback. To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interestingand lucrative!careers in some of todays hottest programming fields. Key Features 2D and 3D vector math Matrices and linear transformations Core concepts from linear algebra Calculus with one or more variables Algorithms for regression, classification, and clustering Interesting real-world examples Written for programmers with solid algebra skills (even if they need some dusting off). No formal coursework in linear algebra or calculus is required. About the technology Most businesses realize they need to apply data science and effective machine learning to gain and maintain a competitive edge. To build these applications, they need developers comfortable writing code and using tools steeped in statistics, linear algebra, and calculus. Math also plays an integral role in other modern applications like game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis. Paul Orland is CEO of Tachyus, a Silicon Valley startup building predictive analytics software to optimize energy production in the oil and gas industry. As founding CTO, he led the engineering team to productize hybrid machine learning and physics models, distributed optimization algorithms, and custom web-based data visualizations. He has a B.S. in mathematics from Yale University and a M.S. in physics from the University of Washington. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…