This repository contains numerical methods for finding solutions of a nonlinear equation as well as to approximate functions from a dataset of (x, y) points.
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Updated
Dec 19, 2020 - Python
This repository contains numerical methods for finding solutions of a nonlinear equation as well as to approximate functions from a dataset of (x, y) points.
An implementation of multilayer perceptron(MLP) on function approximation.
A short and sweet library handling uncertainty in calculations. Can use both standard, probabilistic uncertainties and maximal uncertainties for arbitrary functions over arbitrary variables.
Dash App for visualizing function approximations by polynomials.
This project is a simple implementation of a neural network with gradient descent optimization from scratch. The goal of this project is to demonstrate how a neural network works and how the gradient descent algorithm can be used to optimize its parameters.
This project involves approximating a function to solve an optimization problem. Functions can often be costly to write in code. Approximating a function can sometimes save time and money. Especially when the code is iterated many times.
Distributed and Asynchronous Algorithm for Smooth High-dimensional Function Approximation using Orthotope B-splines
MLP network for approximating functions: implementation and experiments
Repository containing python notebooks used to teach the lab classes of the curricular unit "Numerical Methods (M2039)" at FCUP, Portugal, in study year 2023/2024
Approximating nonlinear functions with low-rank spiking networks
Seminar project at FER led by Assistant Professor Marko Čupić
Simple linear regressor that tries to approximate a simple function deployed in Tensorflow 2.0 without Keras
Assignments and Reading Material for RL Course
This is a reposatory for implementation of different types of optimizers (SGD, RMSprop, Adam etc.) with three different use cases Function Approximation, Multi-class Single-label Classification and Multi-class Multi-label Classification)
Reinforcement Learning algorithms
My Machine Learning course projects
Approximate a function in a single qubit using data-reuploading.
Function approximation using Multilayer Perceptron (MLP)
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