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naxda Goto Github PK

followers: 1.0 following: 24.0 repos: 129.0 gists: 1.0

Type: User

Company: Samsung Electronics

Bio: 하기 싫어도 해라, 감정은 사라지고 결과는 남는다.

Location: South Korea

naxda's Projects

convolutional-neural-network

CNN Tutorial 190703 / 김준모교수님

convolutional-neural-network-2

Neural Style Transfer (Image Style Transfer) 190704 / 김준모교수님

courseraml

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

covid-19-casestudy-and-predictions

This repository is a case study, analysis and visualization of COVID-19 Pandemic spread along with prediction models.

darknet

YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

data-science-career-development

resources for career development in data science

deep-anomaly-detection

Deep Anormaly Detection Practice 190716 / 김종환교수님

deep-learning

Repo for the Deep Learning Nanodegree Foundations program.

deep-learning-chips

190731-190801 / 유희준교수님

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-neural-network-with-tensorflow

Bearing Cleassification 190701 / 이용훈교수님

deep_learning

비전공생도 한눈에 이해하는 딥러닝 자료모음

deep_learning_basic

Deep Learning Basic

defect-detection

20190717 / 김준모교수님

dfdnet

Blind Face Restoration via Deep Multi-scale Component Dictionaries (ECCV 2020)

exoplanets-discovery-machine-learning

Designed a supervised learning model to discover exoplanets thanks to the Kepler Telescope data. This project involved pre-processing data with Dynamic Time Wrapping and applying different unsupervised learning algorithms to make a prediction about a planet. Discovered 144 planets that were not previously categorized as confirmed.

fast-autoaugment

Official Implementation of 'Fast AutoAugment' in PyTorch.

fastbook

Draft of the fastai book

front-end-interview-handbook

🕸 No-bullshit answers to the famous h5bp "Front-end Job Interview Questions"

gan-sandbox

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

generative-adversarial-network

DCGAN Tutorial 190705 / 김준모교수님

generative_inpainting

DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral

hands-on-machinelearning

Let's make good things!

hands-on-ml

Hands-On Machine Learning

handson-ml

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

hbm-and-machine-learning-for-semiconductor

190730 / 김정호교수님

help2019_breast_cancer_1st_solution

1st place solution to the Breast Cancer Classification Task of HeLP Challenge 2019.

homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

homework

Assignments for CS294-112.

i-want-to-study-data-science

데이터 사이언스를 공부하고 싶은 분들을 위한 글

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