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semifinalplc

Program ini adalah program yang kami buat pada saat Semifinal PLC Omron Competition PNJ. Terdiri dari Ladder dan juga HMI nya.

sentimentanalyzenaivebayes

Analisis Sentimen menggunakan metode Naive Bayes dengan "One time learning" dan "Continuous Learning"

sharpen-algorithm-c-sharp

Sharpen your algorithm thinking by make it faster and faster. This is C# version.

singleton-pattern-c-sharp

Repository Manager with SIngletonPattern

skinbased-databasegenerator

This program can generate image for create databases.

state-pattern-c-sharp

store-stock-application-using-c-sharp

storestock-webservice-nancy

strategy-pattern-c-sharp

The Strategy Pattern using C#

tailwind-starter-kit

Tailwind Starter Kit a beautiful extension for TailwindCSS, Free and Open Source

tea-eye

File Tugas Akhir yang warbyasahhhh. Main catur pakai gestur tangan, metode HSV color thresholding + CNN

template-method-pattern-c-sharp

test-app-exe

This is an exe file to test in windows

thesis-experiment-001

IndoBERT - SQuAD Indonesia

thread-pool-learning

truckandcarwithwebcamtest

This is a training example for classification between truck and car. I will uploaded training and validation database soon when connected to WiFi..

tweet-automation-project

An open-source project control Tweet using automation tools. Build with C# Windows Form for running in Windows Desktop.

twitter-search-api-v2

Twitter Search API v2 Implementation using Python Request

unsupervised-multi-hop-qa

Codes for NAACL 2021 Paper "Unsupervised Multi-hop Question Answering by Question Generation"

unsupervised-qa

Template-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering

unsupervised-sirah-nabawiyah-qa

unsupervisedqa

Unsupervised Question answering via Cloze Translation (Indonesian Version)

vdi

virtual-signature

Virtual Signature on The Air using C++ OpenCV and C#

yolov7-training

A clean, modular implementation of the Yolov7 model family, which uses the official pretrained weights, with utilities for training the model on custom (non-COCO) tasks.