Name: Rohitash Chandra
Type: User
Company: UNSW Sydney
Bio: Research interests include the methodologies and applications of Artificial Intelligence and Machine Learning. rohitash-chandra.github.io
Location: Sydney, Australia
3s
3S stands for Stream Sediment Samples
abc
Approximate Bayesian Computation
bayesian-neural-transfer-learning
Bayesian Neural Transfer Learning
bayesian-neuroevolution
Bayesian neuroevolution via MCMC-EA
bayesian_logisticregression
Bayesian logistic regression with MCMC from scratch
bayesianlogisticreg_multioutputs
Bayesian logistic regression for multi-class and multioutput problems with Langevin-gradient MCMC
cmtl-patternclassification
Feature space developmental learning for dynamic and modular pattern classification
cmtl-prnn
Coevolutionary Multi-Task learning Predictive Recurrence Neural Network for Multi-Step Ahead Prediction
cmtl_dynamictimeseries
Coevolutionary Multi-task learning for Dynamic Time Series prediction
convnetjs
Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.
cooperative-coevolution-cmaes
Cooperative Coevolution with CMAES as Sub-Population
cooperativecoevolution
Cooperative Coevolution using Generalised Generation Gap with Parent-Centric Crossover (G3PCX)
cooperativecoevolution-rnn
Cooperative Coevolution Recurrent Neural Network
data-machinelearning-math5836
DataMining MATH5836 @UNSW
decomposedmcmc
Using Markov Chain Monte Carlo to adapt decomposed neural network components for time series prediction
ensemble_bnn
Ensemble Bayesian Feedforward Networks via MCMC Random-Walk
feedforward-neural-network
Feedforward Neural Network with Vanilla Backpropagation
fnn_basic
Feedforward Neural Network: Basic implementation in Python
fnn_sgd
Feedforward neural network with stochastic gradient descent
fnn_timeseries
Feedforward Neural Network (Stochastic Gradient Descent) for Time Series Prediction
g3-pcx-evolutionary-alg
G3-PCX Evolutionary Algorithm in OOP
g3pcx-evoalg-py
G3-PCX Evolutionary Alg in Python
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
kanga
MCMC diagnostics in Python
keras
R Interface to Keras
ld_bnn_pc
Langevin-Dynamics Bayesian Neural Network using MCMC for pattern classification.
ldmcmc_timeseries
Bayesian Learning via Langevin Dynamics (LD-MCMC) for Feedforward Neural Network for Time Series Prediction
logistic_regression
Logistic regression with gradient descent
logisticregression_multiclass
Logistic regression with gradient descent for multi-class classification from scratch
machine-learning-by-andrew-ng-in-python
Documenting my python implementation of Andrew Ng's Machine Learning course
React
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
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
Django
The Web framework for perfectionists with deadlines.
Laravel
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.
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft
Open source projects and samples from Microsoft.
Google
Google ❤️ Open Source for everyone.
Alibaba
Alibaba Open Source for everyone
D3
Data-Driven Documents codes.
Tencent
China tencent open source team.
