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Math for Programmers
Taschenbuch von Paul Orland
Sprache: Englisch

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Beschreibung

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.

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.

Über den Autor
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.
Inhaltsverzeichnis
table of contents
READ IN LIVEBOOK1LEARNING MATH WITH CODE
PART 1: VECTORS AND GRAPHICS
READ IN LIVEBOOK2DRAWING WITH 2D VECTORS
READ IN LIVEBOOK3ASCENDING TO THE 3D WORLD
READ IN LIVEBOOK4TRANSFORMING VECTORS AND GRAPHICS
READ IN LIVEBOOK5COMPUTING TRANSFORMATIONS WITH MATRICES
READ IN LIVEBOOK6GENERALIZING TO HIGHER DIMENSIONS
READ IN LIVEBOOK7SOLVING SYSTEMS OF LINEAR EQUATIONS
PART 2: CALCULUS AND PHYSICAL SIMULATION
READ IN LIVEBOOK8UNDERSTANDING RATES OF CHANGE
READ IN LIVEBOOK9SIMULATING MOVING OBJECTS
READ IN LIVEBOOK10WORKING WITH SYMBOLIC EXPRESSIONS
READ IN LIVEBOOK11SIMULATING FORCE FIELDS
READ IN LIVEBOOK12OPTIMIZING A PHYSICAL SYSTEM
READ IN LIVEBOOK13ANALYZING SOUND WAVES WITH A FOURIER SERIES
PART 3: MACHINE LEARNING APPLICATIONS
READ IN LIVEBOOK14FITTING FUNCTIONS TO DATA
READ IN LIVEBOOK15CLASSIFYING DATA WITH LOGISTIC REGRESSION
READ IN LIVEBOOK16TRAINING NEURAL NETWORKS
APPENDIXES
READ IN LIVEBOOKAPPENDIX A: GETTING SET UP WITH PYTHON
READ IN LIVEBOOKAPPENDIX B: PYTHON TIPS AND TRICKS
READ IN LIVEBOOKAPPENDIX C: LOADING AND RENDERING 3D MODELS WITH OPENGL AND PYGAME
Details
Erscheinungsjahr: 2021
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 650
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781617295355
ISBN-10: 1617295353
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Orland, Paul
Hersteller: Manning Publications
Maße: 232 x 186 x 31 mm
Von/Mit: Paul Orland
Erscheinungsdatum: 02.03.2021
Gewicht: 1,118 kg
preigu-id: 121071376
Über den Autor
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.
Inhaltsverzeichnis
table of contents
READ IN LIVEBOOK1LEARNING MATH WITH CODE
PART 1: VECTORS AND GRAPHICS
READ IN LIVEBOOK2DRAWING WITH 2D VECTORS
READ IN LIVEBOOK3ASCENDING TO THE 3D WORLD
READ IN LIVEBOOK4TRANSFORMING VECTORS AND GRAPHICS
READ IN LIVEBOOK5COMPUTING TRANSFORMATIONS WITH MATRICES
READ IN LIVEBOOK6GENERALIZING TO HIGHER DIMENSIONS
READ IN LIVEBOOK7SOLVING SYSTEMS OF LINEAR EQUATIONS
PART 2: CALCULUS AND PHYSICAL SIMULATION
READ IN LIVEBOOK8UNDERSTANDING RATES OF CHANGE
READ IN LIVEBOOK9SIMULATING MOVING OBJECTS
READ IN LIVEBOOK10WORKING WITH SYMBOLIC EXPRESSIONS
READ IN LIVEBOOK11SIMULATING FORCE FIELDS
READ IN LIVEBOOK12OPTIMIZING A PHYSICAL SYSTEM
READ IN LIVEBOOK13ANALYZING SOUND WAVES WITH A FOURIER SERIES
PART 3: MACHINE LEARNING APPLICATIONS
READ IN LIVEBOOK14FITTING FUNCTIONS TO DATA
READ IN LIVEBOOK15CLASSIFYING DATA WITH LOGISTIC REGRESSION
READ IN LIVEBOOK16TRAINING NEURAL NETWORKS
APPENDIXES
READ IN LIVEBOOKAPPENDIX A: GETTING SET UP WITH PYTHON
READ IN LIVEBOOKAPPENDIX B: PYTHON TIPS AND TRICKS
READ IN LIVEBOOKAPPENDIX C: LOADING AND RENDERING 3D MODELS WITH OPENGL AND PYGAME
Details
Erscheinungsjahr: 2021
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 650
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781617295355
ISBN-10: 1617295353
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Orland, Paul
Hersteller: Manning Publications
Maße: 232 x 186 x 31 mm
Von/Mit: Paul Orland
Erscheinungsdatum: 02.03.2021
Gewicht: 1,118 kg
preigu-id: 121071376
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