What is optimization?

Optimization is the act of selecting the best possible option to solve a mathematical problem when choosing from a set of variables. The concept of optimization has existed in mathematics for centuries, but in more recent times, scientists have discovered that other scientific disciplines have common elements, so the idea of optimization has carried over into other areas of study from engineering to economics to physics to biology. Optimization seeks to discover the maximum or minimum of a function to best solve a problem. It involves variables, constraints, and the objective function, or the goal that drives the solution to the problem. For example, in physics, an optimization problem might seek to discover the minimum amount of energy needed to achieve a certain objective. The advent of sophisticated computers has allowed mathematicians to achieve optimization more accurately across a wide range of functions and problems.

Why learn optimization?

Optimization helps data scientists and computer systems process data more effectively, estimate how many resources it will take to solve a problem, and search for the best solution based on the data available. These features make optimization a key tool that can help those who collect and analyze data. The methods of optimization work hand in hand with statistics and linear algebra to help you understand and process large amounts of data. Solving complex problems that rely on data becomes much easier when you apply the methods and formulas of optimization to them, which makes it essential for machine learning. In fact, today's computer science relies heavily on the relationship between machine learning and optimization. The principles of optimization apply in a different way in business, because nearly every business decision centers on maximizing or minimizing various factors and outcomes.

How can online courses on Coursera help me learn optimization?

When you study optimization with online courses on Coursera, you can gain a broad base of knowledge as well as applications that allow you to put what you learn into practice. Beginning courses include those in which you learn the basics of optimization, whereas more advanced courses go deeper into topics like stochastic processes, machine learning through specific applications, or how to estimate financial models.

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Optimization

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Результатов для запроса ''optimization': 176

Бесплатно
Бесплатно
Imperial College London
Mathematics for Machine Learning
Получаемые навыки: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Deep Learning, Differential Equations, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Optimization, Mathematical Theory & Analysis, Mathematics, Matrices, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science
4.6
(рецензий: 12.9k)
Beginner · Specialization · 3-6 Months
Бесплатно
National Taiwan University
Operations Research (2): Optimization Algorithms
Получаемые навыки: Theoretical Computer Science, Operations Research, Transportation Operations Management, Research and Design, Strategy and Operations, Mathematics, Mathematical Optimization, Linearity, Algebra, Linear Algebra, Supply Chain and Logistics
4.8
(рецензий: 37)
Intermediate · Course · 1-3 Months
Бесплатно
University of Colorado Boulder
Advanced Business Analytics
Получаемые навыки: Algorithms, Analysis, Analytics, Applied Machine Learning, Artificial Neural Networks, Big Data, Business Analysis, Business Analytics, Cloud Computing, Computer Vision, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Clustering Algorithms, Data Management, Data Visualization, Databases, Exploratory Data Analysis, General Statistics, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematical Theory & Analysis, Plot (Graphics), Probability & Statistics, Regression, SQL, Spreadsheet Software, Statistical Analysis, Statistical Programming, Theoretical Computer Science
4.6
(рецензий: 4.8k)
Intermediate · Specialization · 3-6 Months
University of Pennsylvania
Fintech: Foundations & Applications of Financial Technology
Получаемые навыки: Algorithms, BlockChain, Business Process Management, Cryptocurrency, Entrepreneurial Finance, Entrepreneurship, FinTech, Finance, Investment Management, Machine Learning, Machine Learning Algorithms, Payments, Regulations and Compliance, Risk Management, Strategy and Operations, Theoretical Computer Science
4.6
(рецензий: 3k)
Beginner · Specialization · 3-6 Months
Бесплатно
Бесплатно
Бесплатно

Результаты поиска, связанного с optimization

optimization for decision making

optimization of sql query tuning and performance

optimization methods in asset management

discrete optimization

portfolio optimization using markowitz model

convex optimization

search engine optimization

pricing strategy optimization

10 самых популярных курсов по запросу optimization

Operations Research (1): Models and Applications: National Taiwan University
Discrete Optimization: The University of Melbourne
Mathematics for Machine Learning: Imperial College London
Operations Research (2): Optimization Algorithms: National Taiwan University
Operations Research (3): Theory: National Taiwan University
Advanced Business Analytics: University of Colorado Boulder
Fintech: Foundations & Applications of Financial Technology: University of Pennsylvania
Basic Modeling for Discrete Optimization: The University of Melbourne
Build a Professional Resume using Canva: Coursera Project Network
离散优化建模高阶篇 Advanced Modeling for Discrete Optimization: The Chinese University of Hong Kong

Навыки, которые вы можете получить здесь: Algorithms

Графики (22)

Математическая Оптимизация (21)

Компьютерная Программа (20)

Структуры Данных (19)

Решение Проблем (19)

Алгебра (12)

Компьютерное Зрение (10)

Дискретная Математика (10)

Теория Графов (10)

Обработка Изображений (10)

Линейная Алгебра (10)

Обучения С Подкреплением (10)

Часто задаваемые вопросы на тему Оптимизация

Optimization is the act of selecting the best possible option to solve a mathematical problem when choosing from a set of variables. The concept of optimization has existed in mathematics for centuries, but in more recent times, scientists have discovered that other scientific disciplines have common elements, so the idea of optimization has carried over into other areas of study from engineering to economics to physics to biology. Optimization seeks to discover the maximum or minimum of a function to best solve a problem. It involves variables, constraints, and the objective function, or the goal that drives the solution to the problem. For example, in physics, an optimization problem might seek to discover the minimum amount of energy needed to achieve a certain objective. The advent of sophisticated computers has allowed mathematicians to achieve optimization more accurately across a wide range of functions and problems.‎
Optimization helps data scientists and computer systems process data more effectively, estimate how many resources it will take to solve a problem, and search for the best solution based on the data available. These features make optimization a key tool that can help those who collect and analyze data. The methods of optimization work hand in hand with statistics and linear algebra to help you understand and process large amounts of data. Solving complex problems that rely on data becomes much easier when you apply the methods and formulas of optimization to them, which makes it essential for machine learning. In fact, today's computer science relies heavily on the relationship between machine learning and optimization. The principles of optimization apply in a different way in business, because nearly every business decision centers on maximizing or minimizing various factors and outcomes.‎
When you study optimization with online courses on Coursera, you can gain a broad base of knowledge as well as applications that allow you to put what you learn into practice. Beginning courses include those in which you learn the basics of optimization, whereas more advanced courses go deeper into topics like stochastic processes, machine learning through specific applications, or how to estimate financial models.‎

Часто задаваемые вопросы предоставляются в ознакомительных целях. Учащимся рекомендуется дополнительно убедиться в том, что интересующие их курсы и другие материалы соответствуют их личным, профессиональным и финансовым потребностям.