9781617295355 - Math for Programmers: 3D Graphics, Machine Learning, and Simulations with Python de Orland, Paul (14 resultados)

paperback. Condición: Good. Paperback. NOT Ex-library. Clean pages and tight binding. Appendices, Index. This item is in good condition. May show moderate signs of use. Previous owner's name on bottom text block. Until further notice, USPS Priority Mail only reliable option for Hawaii. Proceeds benefit the Pima County Public Library system, which serves Tucson and southern Arizona.

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Paperback. Condición: 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.

Paperback. Condición: New.

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

Condición: New. In.

Paperback. Condición: 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.

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

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

Condición: 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.

Paperback. Condición: 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. Condición: Neu. Neuware - Explore important mathematical concepts through hands-on coding. Purchase of the print book includes a free Elektronisches Buch in PDF, Kindle, and ePub formats from Manning Publications. 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 today's hottest programming fields. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you'll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interestingand lucrative!careers in some of today's hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you'll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks.

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Paperback. Condición: 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.