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Search results for machine learning gradient
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128 search results found
Gradient Energy Matching
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17
Manuscript and code for the paper "Gradient Energy Matching for Distributed Asynchronous Gradient Descent".
Le
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17
Machine Learning Framework
Gbm Intro
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16
GBM intro talk (with R and Python code)
Whitebox Part1
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16
In this part, i've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
Ml_from_scratch
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16
Implementation of basic ML algorithms from scratch in python...
Draco
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15
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Vanillaml
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14
A vanilla machine learning library in Python
Ngboost Experiments
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14
Play around with NGBoost and compare with LightGBM and XGBoost
Snake.ai
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14
Multiplayer snake AI
Coursera Machine Learning
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14
MATLAB assignments in Coursera's Machine Learning course
Torch Reparametrised Mixture Distribution
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14
PyTorch implementation of the mixture distribution family with implicit reparametrisation gradients.
Oxygenjs
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13
This a JavaScript Library for the Numerical Javascript and Machine Learning
Mlday18
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13
Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18
Multivariate Linear Regression Gradient Descent Javascript
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13
⭐️ Multivariate Linear Regression with Gradient Descent in JavaScript (Vectorized)
Logistic Regression Gradient Descent Javascript
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12
⭐️ Logistic Regression with Gradient Descent in JavaScript
Starboost
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11
⭐🚀 Gradient boosting on steroids
Minimize
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11
Conjugate gradients minimization
Swiftxgboost
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11
Swift wrapper for XGBoost gradient boosting machine learning framework with Numpy and TensorFlow support.
Gradflow
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10
A small, educational autograd system with deep neural networks support
Cs229 Machine Learning Solar Energy Predictions
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10
Predicting solar energy using machine learning (LSTM, PCA, boosting). This is our CS 229 project from autumn 2017. Report and poster are included.
Pyreinforce
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10
Deep Reinforcement Learning library for Python
Tutorial Machine Learning Based Survival Analysis
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9
This repository is a tutorial about survival analysis based on advanced machine learning methods including Random Forest, Gradient Boosting Tree and XGBoost. All of them are implemented in R.
Niml
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9
Machine learning in nim
Movie Recommendation
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9
Rlin200lines
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9
PyTorch implementations of Reinforcement Learning algorithms in less than 200 lines
Ovis
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9
Official code for the "Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds"
Univariate Linear Regression Gradient Descent Javascript
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9
⭐️ Univariate Linear Regression with Gradient Descent in JavaScript (Vectorized)
Library
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9
Paper reading list
Machine Learning From Scratch
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9
Easy implementations of ML algorithm in Python code from scratch
Linear Region Attack
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8
A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturbations without doing gradient descent
Object Detection Segmentation
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8
How to run object detection models on Gradient including re-training and inference
Simple Gradient Boosting
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8
Very simple and short implementation of gradient boosting in 18 lines of code
Jsalgos
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8
A collection of algorithms done in JavaScript with visual demos
Multi Classification Logistic Regression Gradient Descent Javascript
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8
⭐️ Multi-Class Classification Logistic Regression with Gradient Descent in JavaScript
Hands On Machine Learning
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8
Machine learning practice based on the book Hands On Machine Learning with Scikit-Learn & Tensorflow by Aurelien Geron.
Nnlib
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8
🎓 Minimal neural networks library developed for educational purposes
Linearsvmclassification
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8
Forest cover type classification/detection using linear support vector machine implemented with gradient descent (from scratch)
Awesome Nonconvex Optimization
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8
A collection of papers and readings for non-convex optimization
Byzantinemomentum
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8
Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)
Mbgdml
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8
Create, use, and analyze machine learning potentials within the many-body expansion framework.
Machinelearning
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7
Adversarial.jl
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7
Adversarial attacks for Neural Networks written with FluxML
Feature Vis Yolov3
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7
Feature visualization tool for YOLOv3, a real-time objection detection algorithm using a deep convolutional network with a Darknet backbone. Visualizes performance attributes via saliency maps to identify how features in the input pixel space influence our network’s predictions in terms of classification and localization
Adaptivedesignprocedure
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7
A design procedure of the training data for Machine Learning algorithms able to iteratively add datapoints according to function discrete gradient
Machine_learning
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7
Machine Learning - Coursera.org
Optiml
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7
Optimizers for/and sklearn compatible Machine Learning models
Tensorflow2.0_notebooks
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6
Implementation of a series of Neural Network architectures in TensorFow 2.0
Learning_to_learn
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6
Learning to learn by gradient descent by gradient descent, Andrychowicz et al., NIPS 2016
Ai_bird
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6
强化学习-游戏AI Trainning
Logistic_regression_numpy
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6
A logistic regressor class written in python, with the testing code against an example dataset.
Ml_linear_regression_interactive
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6
Machinelearning Logisticregressionwithgradientdescentornewton
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6
Demonstrating solving Logistic regression using Gradient Descent or Newton Raphson optimisation with regularisation in Python.
Docs
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6
Machine Learning Codebook
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6
Machine Learning Tutorial for those who are interested in ML
Coursera Uw Machine Learning Classification
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6
Notebook for quick search
Sparkstreaming Network Anomaly Detection
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5
This repository includes supervised and unsupervised machine learning methods which are used to detect anomalies on network datasets. Decision Tree, Random Forest, Gradient Boost Tree, Naive Bayes, and Logistic Regression were used for supervised learning. K-Means was used for unsupervised learning.
Coursera Machine Learning And Practice
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5
A study recording of Coursera's Machine Learning by Andrew Ng, but added some practices for reinforceing learning.
Ai Backpropagation Continued
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5
This section explores a few of the problems (and solutions) to neural networks and backpropagation.
Ultrametric Fitting
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5
Ultrametric Fitting by Gradient Descent
Gradient Descent Optimization
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5
a python script of a function summarize some popular methods about gradient descent
Ml Series Source
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5
Source code for my ML blog series. Intro: http://benbrostoff.github.io/2017/09/19/why-ml
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