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machine_learning_refined

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

machinelearningnotes

Notes for the courses in the Machine Learning Specialization created by the University of Washingtion on Coursera

manifold-diffusion

Diffusion on manifolds for image retrieval

map

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

mario_vs_wario

Image classification problem with screenshots from two GameBoy games.

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

mean-teacher

A state-of-the-art semi-supervised method for image recognition

megatron

meshrcnn

code for Mesh R-CNN, an academic publication, presented at ICCV 2019

meta-learning-papers

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

metric-learning-divide-and-conquer

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019

metric-transfer.pytorch

Deep Metric Transfer for Label Propagation with Limited Annotated Data

metric_learning

Metric Learning (npair loss & angular loss) on mnist and Visualizing by t_SNE

metrics

Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

mingpt

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

mipr

MapReduce Image Processing framework for Hadoop

mish-cuda

Mish Activation Function for PyTorch

mixed_precision_references

Personal collection of references for high performance mixed precision training.

mixup

Implementation of the mixup training method

mixup-generator

An implementation of "mixup: Beyond Empirical Risk Minimization"

mixup_pytorch

A PyTorch implementation of the paper Mixup: Beyond Empirical Risk Minimization in PyTorch

ml-aesthetics-nima

A PyTorch NIMA Implementation using DenseNet. NIMA is a research endeavor that rates the aesthetic quality of images

ml-course-hse

Машинное обучение на ФКН ВШЭ

ml-course-msu

Lecture notes and code for Machine Learning practical course on CMC MSU

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from data mining to deep learning.

ml-minor-hse

ml-mipt

Machine learning course at MIPT

ml-sghmc

Experiment code for Stochastic Gradient Hamiltonian Monte Carlo

ml-sklearn

Tutorials on Machine Learning with Scikit-Learn

mlcourse.ai

Open Machine Learning Course