KanzulF

Pinned Repositories

kalkulator
Language:Python01
mini-project
Language:Python01
PBO-Game
Sebagai repository project PBO pembuatan game
Language:Python00
Burning-Heroes
PBO 2nd Project
Language:Python00
Native-MVC-PHP
MVC website with Native PHP
Language:PHP00
blackeye
The most complete Phishing Tool, with 32 templates +1 customizable
Language:HTML10
a163-bfwd-labs
00
BangkitCapstone2022
Language:Python00
BelajarLaravel
Language:PHP00
button-python-click
Language:Python00

KanzulF's Repositories

KanzulF/ByteBuilders
KanzulF/KAMI-test
Language:PHP
KanzulF/multi-select-tag
KanzulF/PbmProjek-RUNPAL
Language:Dart
KanzulF/KSProjek-NoteDairy
Language:Dart
KanzulF/BelajarLaravel
Language:PHP
KanzulF/masif-dashboard-laravel
Language:PHP
KanzulF/escm
e-scm by django4
Language:CSS
KanzulF/BangkitCapstone2022
Language:Python
KanzulF/kalkulator
Language:Python1
KanzulF/studentCode
this Repo just for studentCode
KanzulF/VolunterPembuatanAplikasi
Repository ini merupakan salah satu studi kasus dari kelas Belajar Dasar Git dengan GitHub.
KanzulF/indonesia-covid-api
KanzulF/capstone_MLFrontEnd
Capstone Project
Language:CSS
KanzulF/jimpitan
KanzulF/testing
KanzulF/button-python-click
KanzulF/GameConsign-Miniproject
KanzulF/KanzulF
My Portofolio Github Account
KanzulF/KanzulF.github.io
Language:HTML
KanzulF/blackeye
The most complete Phishing Tool, with 32 templates +1 customizable
1
KanzulF/Native-MVC-PHP
MVC website with Native PHP
KanzulF/Burning-Heroes
PBO 2nd Project
KanzulF/indonlu
The first-ever vast natural language processing benchmark for Indonesian Language. We provide multiple downstream tasks, pre-trained IndoBERT models, and a starter code! (AACL-IJCNLP 2020)
KanzulF/quiz2pbw
Language:PHP
KanzulF/PBO-Game
Sebagai repository project PBO pembuatan game
Language:Python
KanzulF/Introduction-to-Machine-Learning
This repo will house all our course material and code snippets from the Introduction to Machine Learning Class
KanzulF/a163-bfwd-labs
KanzulF/mini-project
Language:Python1
KanzulF/nlp-in-tfjs
This example demonstrated loading a model and using it in the browser. This model is trained to predict the sentiment of a short restaurant review (as a score between 0 and 1). The training is done server side using Python and then converted into a TensorFlow.js model. The model is trained using YELP reviews that have been truncated to a maximum of 18 words, only the 2000 most used words in the reviews are used. You can experiment with the model on this page.