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Linear programming, mathematical modeling technique in which a linear function is maximized or minimized when subjected to various constraints. This technique has been useful for guiding quantitative decisions in business planning, in industrial engineering, and—to a lesser extent—in the social and physical sciences.
 Course related:
 AAE3009 Operations Research and Computational Analytics in Air Transport Operations
 Subjects:
 Mathematics and Statistics
 Keywords:
 Linear programming
 Resource Type:
 Others

Others
In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.
 Course related:
 AMA1600 Fundamentals of AI and Data Analytics and AMA1751 Linear Algebra
 Subjects:
 Mathematics and Statistics and Computing
 Keywords:
 Computer programming Computer science Python (Computer program language)
 Resource Type:
 Others

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We offer mathematics in an enjoyable and easytolearn manner, because we believe that mathematics is fun.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Mathematics
 Resource Type:
 Others

Others
Fuzzy Logic Toolbox™ provides MATLAB® functions, apps, and a Simulink® block for analyzing, designing, and simulating systems based on fuzzy logic. The product guides you through the steps of designing fuzzy inference systems. Functions are provided for many common methods, including fuzzy clustering and adaptive neurofuzzy learning. The toolbox lets you model complex system behaviors using simple logic rules, and then implement these rules in a fuzzy inference system. You can use it as a standalone fuzzy inference engine. Alternatively, you can use fuzzy inference blocks in Simulink and simulate the fuzzy systems within a comprehensive model of the entire dynamic system.
 Course related:
 SD5804 Design Research Methods
 Subjects:
 Computing and Mathematics and Statistics
 Keywords:
 Fuzzy systems Fuzzy logic
 Resource Type:
 Others

Others
Numerical methods are techniques to approximate mathematical procedures (e.g., integrals). Approximations are needed because we either cannot solve the procedure analytically (e.g., the standard normal cumulative distribution function) or because the analytical method is intractable (e.g., solving a set of a thousand simultaneous linear equations for a thousand unknowns). By end of this course, participants will be able to apply the numerical methods for the following mathematical procedures and topics: differentiation, nonlinear equations, and simultaneous linear equations, interpolation, regression, integration, and ordinary differential equations. Additionally, they will be able to calculate errors and implement their relationship to the accuracy of the numerical solutions. To be prepared for this course, students should have a passing grade in introductory physics, integral calculus, differential calculus, and ordinary differential equations.
 Course related:
 BSE3302 Computer Methods in Building Services Engineering
 Subjects:
 Mathematics and Statistics
 Keywords:
 Numerical analysis Numerical calculations
 Resource Type:
 Others

Others
Nicholas John Higham FRS is a British numerical analyst. He is Royal Society Research Professor and Richardson Professor of Applied Mathematics in the School of Mathematics at the University of Manchester. In this blog, it covers the popular topic, such as: (1) Top 5 Beamer Tips (2) The Nearest Correlation Matrix (3) The Top 10 Algorithms in Applied Mathematics (4) A Black Background for More Restful PDF viewing (5) Typesetting Mathematics According to the ISO Standard (6) Fourth Edition (2013) of Golub and Van Loan’s Matrix Computations (7) The Rise of Mixed Precision Arithmetic (8) Second Edition (2013) of Matrix Analysis by Horn and Johnson (9) Half Precision Arithmetic: fp16 Versus bfloat16 (10) Managing BibTeX Files with Emacs (11) Five Examples of Proofreading (12) Implicit Expansion: A Powerful New Feature of MATLAB R2016b (13) Dot Grid Paper for Writing Mathematics (14) Programming Languages: An Applied Mathematics View (15) Three BibTeX Tips (16) Better LaTeX Tables with Booktabs (17) The Princeton Companion to Applied Mathematics (18) Numerical Methods That (Usually) Work (19) What’s New in MATLAB R2017a? (20) What Is Numerical Stability?
 Course related:
 AMA615 Nonlinear Optimization Methods and AMA611 Applied Analysis
 Subjects:
 Mathematics and Statistics
 Keywords:
 Computer programming Numerical analysis
 Resource Type:
 Others

Others
This sequence is ideal for students or early data science professionals who want to strengthen their knowledge of fundamental probability and statistics concepts. Mastery of Mathematical Fundamentals is a prerequisite.
 Course related:
 AMA1110 Basic Mathematics I – Calculus and Probability & Statistics
 Subjects:
 Finance and Mathematics and Statistics
 Keywords:
 Probabilities Mathematical statistics Business mathematics
 Resource Type:
 Others

Others
This learning material covers the topic of differentiation by considering first principles (gradients of chords and tangents).
 Course related:
 AMA1110 Basic Mathematics I – Calculus and Probability & Statistics
 Subjects:
 Mathematics and Statistics
 Keywords:
 Differential calculus
 Resource Type:
 Others

Others
Our calculator allows you to check your solutions to calculus exercises. It helps you practice by showing you the full working (step by step integration). All common integration techniques and even special functions are supported. The Integral Calculator supports definite and indefinite integrals (antiderivatives) as well as integrating functions with many variables. You can also check your answers! Interactive graphs/plots help visualize and better understand the functions.
 Course related:
 AMA1120 Basic Mathematics II  Calculas and Linear Algebra
 Subjects:
 Mathematics and Statistics
 Keywords:
 Calculus Integral
 Resource Type:
 Others

Others
Math explained in easy language, plus puzzles, games, worksheets and an illustrated dictionary.
 Course related:
 AMA1110 Basic Mathematics I – Calculus and Probability & Statistics and AMA1120 Basic Mathematics II – Calculus and Linear Algebra
 Subjects:
 Mathematics and Statistics
 Keywords:
 Mathematics
 Resource Type:
 Others