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Language-Adversarial Training for Cross-Lingual Text Classification (TACL)
A Fair Classifier based on Adversarial Debiasing
This is an implementation of alexnet based malware image based malware image classification
Algorithms for explaining machine learning models
This repository of codes includes in the R and Python programs used in the six chapters of my published book titled "Analysis and Forecasting of Financial Time Series: Selected Cases". The book is published by Cambridge Scholars Publishing, New Casle upon Tyne, United Kindoam, in 2022.
A swedish banking application for your Android device.
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
Amharic Sentiment Annotator Bot
-Generating Irish Folk Tunes and Lyrics - using LSTM, this project uses Long Short-term Memory (LSTM) -based recurrent neural network (RNN) to generate music and lyrics using the Irish Folk Music dataset. Additionally, it also generates "Bob Dylan-esque" lyrics, using all of Bob Dylan's songs. -Technologies used- AWS, Deep Learning, Python.
A curated list of awesome Fairness in AI resources
The bAbI question-answering dataset ported into T2T.
A from-scratch implementation of image classification system using Harris detector and Bag of words method.
BatBat :battery: :zap: is an easy and free Maven Java game run in Spring Boot.
MATLAB example using deep learning to classify chronological age from brain MRI images
Breast tumor detection using convolutional neural networks( a binary classifier of mammogram images "Normal", "Abnormal (Tumor)")
A Deep Learning Based approach for diagnosis of Schizophrenia using EEG brain recordings
Brain Tumor Classification for MR Images using Transfer Learning and Fine-Tuning
Deep Reinforcement Learning Agent for Artari's Cart-Pole Game
100-Digit Competition. This folder includes GECCO 2019 and SEMCCO 2019 too, in addition to CEC 2019
All nature-inspired algorithms involve two processes namely exploration and exploitation. For getting optimal performance, there should be a proper balance between these processes. Further, the majority of the optimization algorithms suffer from local minima entrapment problem and slow convergence speed. To alleviate these problems, researchers are now using chaotic maps. The Chaotic Gravitational Search Algorithm (CGSA) is a physics-based heuristic algorithm inspired by Newton's gravity principle and laws of motion. It uses 10 chaotic maps for global search and fast convergence speed. Basically, in GSA gravitational constant (G) is utilized for adaptive learning of the agents. For increasing the learning speed of the agents, chaotic maps are added to gravitational constant. The practical applicability of CGSA has been accessed through by applying it to nine Mechanical and Civil engineering design problems which include Welded Beam Design (WBD), Compression Spring Design (CSD), Pressure Vessel Design (PVD), Speed Reducer Design (SRD), Gear Train Design (GTD), Three Bar Truss (TBT), Stepped Cantilever Beam design (SCBD), Multiple Disc Clutch Brake Design (MDCBD), and Hydrodynamic Thrust Bearing Design (HTBD). The CGSA has been compared with seven state of the art stochastic algorithms particularly Constriction Coefficient based Particle Swarm Optimization and Gravitational Search Algorithm (CPSOGSA), Standard Gravitational Search Algorithm (GSA), Classical Particle Swarm Optimization (PSO), Biogeography Based Optimization (BBO), Continuous Genetic Algorithm (GA), Differential Evolution (DE), and Ant Colony Optimization (ACO). The experimental results indicate that CGSA shows efficient performance as compared to other seven participating algorithms.
This example shows how to train a deep neural network to classify SARS COVID-19 and other lung infections using chest X-ray (CXR) images.
Use of computer vision and deep learning methods to create CNN for classifying Psoriasis and Eczema from image data set with varied levels of skin pigment
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
Codes for some of my co-authored journal/conference papers
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
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.