Optimization: principles and algorithms - Linear optimization
- 0.0
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Brief Introduction
Introduction to linear optimization, duality and the simplex algorithm.
Description
Introduction to linear optimization, duality and the simplex algorithm.
Knowledge
- The course is structured into 5 sections.
- Formulation: you will learn from simple examples how to formulate, transform and characterize an optimization problem.
- Constraints: you will learn how to represent the constraints of a linear optimization problem, both from a geometric and algebraic point of views.
- Duality: you will learn how to derive a companion problem called the "dual".
- Optimality conditions: you will learn sufficient and necessary conditions for an optimal solution.
- Simplex method: you will learn an algorithm to solve a linear optimization problem.
Machine Learning and AI: Support Vector Machines in Python
- 4.6
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Artificial Intelligence and Data Science Algorithms in Python for Classification and Regression The toughest obstacle to overcome when you’re learning about support vector machines is that they are very theoretical....
Introduction to Accounting Data Analytics and Visualization
- 4.8
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Accounting has always been about analytical thinking. From the earliest days of the profession, Luca Pacioli emphasized the importance of math and order for analyzing business transactions....
Build Regression, Classification, and Clustering Models
- 0.0
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In most cases, the ultimate goal of a machine learning project is to produce a model. Build Linear Regression Models Using Linear Algebra...
Learn User Experience Design from A-Z: Adobe XD UI/UX Design
- 4.5
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Learn how to become a professional UX/UI Designer and create beautiful websites and applications from scratch. Welcome to the Learn User Experience Design from A-Z: Adobe XD UI UX Design...
