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Gorgonia is a library that helps facilitate machine learning in Go.
Fast and Easy Infinite Neural Networks in Python
OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN
🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types
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.
Image morphing without reference points by applying warp maps and optimizing over them.
The simplest form of an artificial neural network explained and demonstrated.
This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
A next-gen Lagrange-Newton (SQP + barrier) solver for nonconvex constrained optimization
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
Implementing Multiple Layer Neural Network from Scratch
A PyTorch implementation of Learning to learn by gradient descent by gradient descent
Implementation of basic ML algorithms from scratch in python...
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.
Six snippets of code that made deep learning what it is today.
👩🏻⚕️Covid-19 estimation and forecast using statistical model; 新型冠状病毒肺炎统计模型预测 (Jan 2020)
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
A curated list of mathematics documents ,Concepts, Study Materials , Algorithms and Codes available across the internet for machine learning and deep learning