Mathematics for Machine Learning Specialization
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Updated
May 14, 2019 - Jupyter Notebook
Mathematics for Machine Learning Specialization
Imperial College London »Mathematics for Machine Learning«. A sequence of 3 courses on the prerequisite mathematics for applications in data science and machine learning. (1) Linear Algebra (2) Multivariate Calculus and (3) Principal Component Analysis (completed Sept. 10th, 2018)
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.
This repository contains a comprehensive collection of mathematical concepts and techniques relevant to various fields of AI, including ML, DL & other areas.It also includes the corresponding source code for all programming tasks associated with the Mathematics for Machine Learning courses, which are taught at Coursera by Imperial College London.
Code to visualize function F(x,y) in 3D space, heat map, contour lines along with line integral visualization
Detailed notes and exercises for the "Mathematics for Machine Learning" specialization of Imperial College London.
Effective HP calculator turned multivariable regression experiment
3d grapher in web-app form.
ICL's Mathematics for Machine Learning specialization, Python assignments.
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
Final Project for Harvard University CS-207 Fall 2022
Monte Carlo 2 Variable Function Domain Approximation
QSD's MVC study.
My personal notes for learning math
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.
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