Qutaiba Al-Nuaimy's repositories
ActiveLabel.swift
UILabel drop-in replacement supporting Hashtags (#), Mentions (@) and URLs (http://) written in Swift
Atributika
Convert text with HTML tags, links, hashtags, mentions into NSAttributedString. Make them clickable with UILabel drop-in replacement.
awesome-for-beginners
A list of awesome beginners-friendly projects.
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
Convolutional-Neural-Network
Implementing a Convolutional Neural Network from scratch
elasticsearch
Free and Open, Distributed, RESTful Search Engine
Error-404
This is a short script that allows you to search StackOverflow for your Python exception(s)
KMeans-Clustering
Implementing KMeans(++) Clustering models from scratch.
Linear-Logistic-Regression
Implementing Linear and Logistic Regression Models from scratch.
multiplicitytech.github.io
a youth-led publication exploring the impact of tech on our selves & societies
naiveproxy
Make a fortune quietly
Neural-Network
Implementing a Neural network from scratch.
ockam
Orchestrate end-to-end encryption, cryptographic identities, mutual authentication, and authorization policies between distributed applications – at massive scale. Use Ockam to build secure-by-design applications that can Trust Data-in-Motion.
ockam-contributors
Contributors to the Ockam Open Source projects
PHONK
PHONK is a self-contained creative scripting toolbox for new and old Android Devices
Principal-Component-Analysis
Implementing Principal Component Analysis (PCA) from scratch.
PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
PyTorch-YOLOv3-AML
under construction - yolov3 pytorch implementation
qxtaiba
personal website (qxtaiba.com)
scrapedin
LinkedIn Scraper (currently working 2020)
Support-Vector-Machine
Implementing a Support Vector Machine (SVM) model from scratch.
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.