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Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

machine-learning calculus linear-regression linear-algebra probability mathematics gradient-descent bayesian-statistics linear-equation mathematical-optimization determinants eigenvalues-and-eigenvectors

Updated Jul 10, 2023
Jupyter Notebook

gy910210 / neural-network-from-scratch

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Implementing Multiple Layer Neural Network from Scratch

neural-network computation-graph gradient-descent

Updated Apr 14, 2016
Python

ikostrikov / pytorch-meta-optimizer

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A PyTorch implementation of Learning to learn by gradient descent by gradient descent

deep-learning pytorch gradient-descent

Updated Aug 27, 2018
Python

hiroyuki-kasai / NMFLibrary

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NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1

matrix-factorization constrained-optimization data-analysis robust-optimization gradient-descent matlab-toolbox clustering-algorithm optimization-algorithms nmf online-learning stochastic-optimizers nonnegativity-constraints orthogonal divergence probabilistic-matrix-factorization nonnegative-matrix-factorization sparse-representations

Updated Feb 24, 2023
MATLAB

Suji04 / ML_from_Scratch

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Implementation of basic ML algorithms from scratch in python...

python linear-regression logistic-regression gradient-descent decision-tree-classifier youtube-channel stochastic-gradient-descent decision-tree-regression k-means-clustering knn-algorithm

Updated Feb 26, 2021
Jupyter Notebook

cvanaret / Uno

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A next-gen Lagrange-Newton solver for nonconvex optimization. It unifies barrier and SQP methods in a modern and generic way, and implements different globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.

cpp optimization constrained-optimization gradient-descent optimization-methods numerical-optimization nonlinear-programming-algorithms nonlinear-optimization optimization-algorithms nonlinear-programming quadratic-programming interior-point-method newton-method continuous-optimization sequential-quadratic-programming mathematical-programming mathematical-optimization nonconvex-optimization local-optimization optimization-solver

Updated Nov 6, 2024
C++

tsycnh / mlbasic

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深度学习常用优化方法详解

sgd momentum gradient-descent minibatch-sgd

Updated Jul 22, 2017
Python

emilwallner / Deep-Learning-From-Scratch

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Six snippets of code that made deep learning what it is today.

deep-learning linear-regression least-squares mnist perceptron gradient-descent backpropagation

Updated Oct 10, 2019
Jupyter Notebook

zeke-xie / deep-learning-dynamics-paper-list

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This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and stochastic optimization. Thus, deep learning dynamics play an essentially important role in theoretical foundation of deep learning.

machine-learning deep-learning optimization gradient-descent