Detailed notes and exercises for the "Mathematics for Machine Learning" specialization of Imperial College London.

in this repository i will upload everything i have learned about mathematics for machine learning. programs should be related to subjects such as linear algebra, calculus, multivariable calculus, statistics and probability.

3d grapher in web-app form.

Monte Carlo 2 Variable Function Domain Approximation

This program saves the hassle of normal computation and computes the velocity, speed, unit tangent vector, curvature, normal vector, bi-normal vector, and torsion of a given position vector.

Lecture summary on multivariable calculus

A Java Library for Higher-Level Mathematics from Scratch - Includes Linear Algebra, Abstract Algbera, Multivariable Calculus, etc

Polynomial analysis module

Final Project for Harvard University CS-207 Fall 2022

Jupyter Notebook defining, visualizing, and executing a gradient descent algorithm for optimization of three-dimensional cost functions.

MCLA notes

Linear regression from scratch.

Mathematics for Machine Learning is a specialisation in which you will master the fundamental mathematical toolkit for machine learning: calculus, linear algebra, statistics, and probability.

My personal notes for learning math

Effective HP calculator turned multivariable regression experiment

3d Vector Field Art Tool

ICL's Mathematics for Machine Learning specialization, Python assignments.

Final Project for Harvard University CS-207 Fall 2022

Creating a neural network from scratch without the use of libraries like TensorFlow, Keras, PyTorch, etc. Only using python math libraries.

Numerical methods and calculator written in C. (Integration and differentiation of several variables and more!). Ultimately turning into a math library at this point with support for multivariable operations. Much thanks to the creator of TinyExpr for ease of expression parsing