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24 search results found

Python For Signal Processing ⭐ 1,170

Notebooks for "Python for Signal Processing" book

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

Speedchallenge ⭐ 54

Vae Pytorch ⭐ 46

AE and VAE Playground in PyTorch

Random Fourier Features

Imgcluster ⭐ 28

Image clustering using the similarity algorithms: SIFT, SSIM, CW-SSIM, MSE

Facial_beauty_prediction ⭐ 26

Sgd From Scratch ⭐ 25

Stochastic gradient descent from scratch for linear regression

Superresgan Keras ⭐ 19

Single-Image Super-Resolution with Generative Adversarial Networks - Keras implementation

Moving_mnist ⭐ 17

Exploring Moving Mnist dataset with forecasting algorithms

Yandex Blitz Ml 2018 ⭐ 15

My solutions of Yandex.Blitz (Yandex Cup) Machine Learning Track 2018

Sanet_implementation ⭐ 14

using tensorflow

Hyperparameters Optimization ⭐ 14

Hyperparameters-Optimization

Brain Mri Autoencoder ⭐ 11

Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brain

Pr Impwork ⭐ 10

This is some implements of pattern classificaion course including perceptron,relaxation procedure,MSE,Fisher,Ho-kashyap,SVM,KNN

The Nature Conservancy Fisheries Monitoring Challenge ⭐ 8

__dl Prediction On Earth Phenology ⭐ 6

佳格天地比赛，时空序列预测，决赛top6方案

I have implemented in both python and R two papers for estimating subgroup means under misclassification, which are useful for data analyses. T. K. MAK, W. K. LI, A new method for estimating subgroup means under misclassification, Biometrika, Volume 75, Issue 1, March 1988, Pages 105–111, https//doi.org/10.1093/biomet/75.1.105 Selén, Jan. “Adjusting for Errors in Classification and Measurement in the Analysis of Partly and Purely Categorical Data.” Journal of the Ameri

Mri_super_resolution ⭐ 5

MRI Super Resolution with a Deep 3D Resnet Variant using Perceptual Loss

Project 3 Dft And Ml ⭐ 5

Predicting speed of cars using optical flow analysis and Convolutional neural networks

Reinforcement_learning ⭐ 5

RL(Reinforcement Learning) with gym, keras

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