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Name: Kabir M Alamgir
Type: User
Name: Kabir M Alamgir
Type: User
A curated repository of software engineering repository mining data sets
A curated list of awesome Python frameworks, libraries, software and resources
Simpler Transfer Learning (Using "Bellwethers"). ARXIV link: https://arxiv.org/abs/1703.06218
Free Ebooks
Cityu LaTeX Presentation
A collection of LaTeX thesis template for students at City University of Hong Kong.
Yet another XeLaTeX thesis template for MPhil, PhD and PD students at City University of Hong Kong.
Algorithms for detecting changes from a data stream.
Generator for classification with concept drift
Cross-project defection prediction tooling
《面向程序员的数据挖掘指南》源码
An R package of Defect Prediction Datasets for Software Engineering Research
Docker - the open-source application container engine
Empirical standards for conducting and evaluating research in software engineering
I have done my individual project (dissertation) on ensemble methods. In which I first did the background study on different ensemble methods and then implemented Boosting, AdaBoost, Bagging and random forest techniques on underlying machine learning algorithms. I used boosting method to boost the performance of weak learner like decision stumps. Implemented bagging for decision trees (both regression and classification problems) and for KNN classifier. Used random forest for classification trees. I have implemented a special algorithm of boosting called “AdaBoost” on logistic regression algorithm using different threshold values. Then plotted the different graphs like an error rate as a function of boosting, bagging and random forest iterations. Compared results of bagging with boosting. Analysed the performance of classifier before applying ensemble methods and after applying ensemble methods. Used different model evaluation techniques like cross-validation, MSE, PRSS, ROC curves, confusion matrix, and out-of-bag error estimation to estimate the performance of ensemble techniques.
:books: Freely available programming books
An implementation of the Grammar of Graphics in R
GitHub Archive is a project to record the public GitHub timeline, archive it, and make it easily accessible for further analysis.
Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)
The personal website framework for Hugo
Book about interpretable machine learning
dataset description
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.