내가 보려고 정리한 <프로그래밍 기초 Ⅰ> / organized for me

Last update: Mar 07, 2022

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Overview

Programming-Basics

프로그래밍 기초 Ⅰ 아카이브

Do it! 점프 투 파이썬

주차	강의주제	비고
1주차	Syllabus
2주차	자료형 - 숫자형
3주차	자료형 - 문자열형
4주차	입력과 출력
5주차	제어문 - 조건문 if
6주차	제어문 - 반복문 while
7주차	module - random
8주차	중간고사
9주차	함수
10주차	module - turtle
11주차	자료형 - container : list, tuple, set
12주차	제어문 - 반복문 for
13주차	자료형 - container : dictionary module - numpy
14주차	module - matplotlib
15주차	기말고사

Owner

KIMMINSEO

PKNU CE 22

GitHub Repository

PyTorch implementation of Munchausen Reinforcement Learning based on DQN and SAC. Handles discrete and continuous action spaces

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Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The original code is written in keras.

CasRel-pytorch-reimplement Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The o

170 Dec 01, 2022

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

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220 Dec 13, 2022

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks

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210 Jan 04, 2023

[ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark Accepted as a spotlight paper at ICLR 2021. Table of content File structure Prerequi

72 Jan 03, 2023

CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels

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0 Jan 21, 2022

A convolutional recurrent neural network for classifying A/B phases in EEG signals recorded for sleep analysis.

CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases

2 Nov 25, 2022

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D

95 Dec 30, 2022

MegEngine implementation of YOLOX

Introduction YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and ind

77 Nov 22, 2022

[CVPR 2021] Generative Hierarchical Features from Synthesizing Images

148 Dec 09, 2022

本项目是一个带有前端界面的垃圾分类项目，加载了训练好的模型参数，模型为efficientnetb4，暂时为40分类问题。

说明本项目是一个带有前端界面的垃圾分类项目，加载了训练好的模型参数，模型为efficientnetb4，暂时为40分类问题。 python依赖 tf2.3 、cv2、numpy、pyqt5 pyqt5安装 pip install PyQt5 pip install PyQt5-tools 使用程

4 May 04, 2022

Introducing neural networks to predict stock prices

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

637 Jan 04, 2023

Code for "Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans" CVPR 2021 best paper candidate

News 05/17/2021 To make the comparison on ZJU-MoCap easier, we save quantitative and qualitative results of other methods at here, including Neural Vo

748 Jan 07, 2023