1419 Open source projects that are alternatives of or similar to SGDLibrary

Matlab library for gradient descent algorithms: Version 1.0.1

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

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

100 Days of ML Coding

I will update this repository to learn Machine learning with python with statistics content and materials

Plain python implementations of basic machine learning algorithms

Simple machine learning library / 簡單易用的機器學習套件

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

MATLAB library for non-negative matrix factorization (NMF): Version 1.8.1

Machine Learning Course @ Santa Clara University

A PureScript, browser-based implementation of simple linear regression.

Python code for common Machine Learning Algorithms

Code for Tensorflow Machine Learning Cookbook

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Tracking, notes and programming snippets while learning predictive analytics

ML algorithm for real-time classification

bitcoin prediction algorithms

Deep Learning From Scratch

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

A simple machine learning framework written in Swift 🤖

A set of machine learning experiments in Clojure

General Assembly's 2015 Data Science course in Washington, DC

A New, Interactive Approach to Learning Python

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

Matlab implementation of the Adam stochastic gradient descent optimisation algorithm

Variational Bayes linear and logistic regression

机器学习-Coursera-吴恩达- python+Matlab代码实现

该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。

subsemble R package for ensemble learning on subsets of data

Alex Castrounis' curated set of resources for artificial intelligence (AI), machine learning, data science, internet of things (IoT), and more.

No description or website provided.

Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥

📈 Regression and Classification with UC Davis student quiz data and exam data

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

A sentiment classifier on mixed language (and mixed script) reviews in Tamil, Malayalam and English

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

Machine Learning Concepts with Concepts

machine learning algorithm

A Python package to build predictive linear and logistic regression models focused on performance and interpretation

Launch machine learning models into production using flask, docker etc.

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

Python library for Bayesian hyper-parameters optimization

A day to day plan for this challenge. Covers both theoritical and practical aspects

Python implementation of Andrew Ng's ML course projects

Bare bone examples of machine learning in TensorFlow

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

.pdf Format Books for Machine and Deep Learning

Tensorflow implementation of preconditioned stochastic gradient descent

SC-Adagrad, SC-RMSProp and RMSProp algorithms for training deep networks proposed in

An introductory statistics course for social scientists, using Stata

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Scala Library/REPL for Machine Learning Research

Reinforcement learning with A* and a deep heuristic

Code for Java Deep Learning Cookbook

Heart Disease prediction using 5 algorithms

Basic Machine Learning implementation with python