Creating an Model for Finding best Prediction
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Updated
Jun 3, 2017 - Jupyter Notebook
Creating an Model for Finding best Prediction
Project 1: Root Finding Methods
Implementation and usage of numerical root-finding algorithms.
First project for DisCont Mathematics 2 @ FER
Three body simulation in terminal.
Likelihood-ratio test for normally distributed populations with non-constant variance. Essentially a LRT equivalent to Welch's ANOVA. Documented in LaTeX, implemented in Python.
Métodos numéricos con python(Numpy, matplotlib, pandas)
This repository is focused in some mathematical modeling techniques, such as, such as Newton`s root method, Bolzano theorem and false-position algorithm.
Python program to approximate square roots using Newton's method
The Babylonian method for finding square roots by hand | Heron's method | Newton's method
Numerical optimization library in C++.
Root-finding algorithms implementation. 2019
A WIP library for performing multi-root searching of one-dimensional transcendental equations using auto-differentiation in Rust
Matlab implementations of approximation of solutions to nonlinear functions
Numerical Algorithms course projects
Implementation of Logistic Regression and Finding optimal coefficient with Intercept using Newton's Method and Gradient Descent method.
Sample Convex Optimization using Gradient Descent, Newton's method and Coordinate Descent
The behaviour of general root-finding algorithms is studied in numerical analysis. How-ever, for polynomials, root-finding study belongs generally to computer algebra, sincealgebraic properties of polynomials are fundamental for the most efficient algorithms. The efficiency of an algorithm may depend dramatically on the characteristics of the gi…
The implementation of advanced mathematical optimization methods
🎓 My university course in numerical analysis from Fedor Sergeevich Peplin. Here you can find some implemented algorithms from this subject with a brief description.
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