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

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, F…

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

Machine learning algorithms in Dart programming language

Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)

Classifying the Blur and Clear Images

Riemannian stochastic optimization algorithms: Version 1.0.3

Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.

Matlab implementation of the Adam stochastic gradient descent optimisation algorithm

Easy-to-use linear and non-linear solver

Exploiting Explainable Metrics for Augmented SGD [CVPR2022]

OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1

Python implementation of stochastic sub-gradient descent algorithm for SVM from scratch

AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)

XCSF learning classifier system: rule-based online evolutionary machine learning

A statistical computations and ML orientated Python package to predict stock price.

Tensorflow implementation of preconditioned stochastic gradient descent

Stochastic gradient descent with model building

Hi! Thanks for checking out my tutorial where I walk you through the process of coding a convolutional neural network in java from scratch. After building a network for a university assignment, I decided to create a tutorial to (hopefully) help others do the same and improve my own understanding of neural networks.

SVM with Learning Using Privileged Information (LUPI) framework