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Mathlads is a foundational mathematical blog aiming to build knowledge from the ground up to broader topics such as AI and ML.
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Series from Mathlads
We have categorized related blog posts and order them in ascending complexity order. Pick a series that you are interested in!
Linear Algebra
Linear algebra is essential for understanding and manipulating multi-dimensional data, making it crucial in fields such as computer graphics, machine learning, and engineering. This series introduces core concepts like vectors, matrices, and linear transformations, which are foundational for advanced mathematical operations and real-world applications. By mastering these basics, you will be equipped to handle complex problems and perform tasks like data analysis and modeling more effectively.
Calculus
Calculus is fundamental for analyzing change and motion, and it is widely used in science, engineering, and economics. This series covers the essential principles of limits, derivatives, and integrals, which form the basis for understanding dynamic systems. Learning calculus will enable you to solve problems involving rates of change, optimize functions, and model real-world phenomena accurately.
Statistics
Statistics is crucial for making data-driven decisions in various fields, including social sciences, business, and healthcare. This series introduces the basics of summarizing data, understanding probability, and making inferences about populations from samples. By learning statistics, you will gain the skills to analyze data, test hypotheses, and draw reliable conclusions, enhancing your ability to make informed decisions.
Numerical Analysis
Many real-world problems can be modeled mathematically into equations. Finding their exact roots value is almost impossible (in fact, proving those equations exists solution alone has been a tough task already). In real life however, approximation of those values is enough to apply in engineering and many other aspects. The background of those approximation techniques is the content of numerical analysis. In this series, we will discover exactly the theory of those knowledge.