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A MNIST-like fashion product database. Benchmark :point_right:
The fast.ai deep learning library, lessons, and tutorials
implementation of FBCSP algorithm
The MATLAB toolbox for MEG, EEG and iEEG analysis
Python scripts for accessing Fitbit API and downloading time-series and daily summary data
Hierarchical Approximate Proper Orthogonal Decomposition
Processed the DEAP dataset on basis of 1) PSD (power spectral density) and 2)DWT(discrete wavelet transform) features . Classifies the EEG ratings based on Arousl and Valence(high /Low)
Code for paper "Application of Convolutional Neural Networks to Four-Class Motor Imagery Classification Problem"
Spectral embedding using Laplacian Eigenmaps
This is the code for "Learn Blockchain in 2 Months" by Siraj Raval on Youtube
This is the Curriculum for "Learn Computer Science in 5 Months" By Siraj Raval on Youtube
This is the Curriculum for "Learn Deep Learning in 6 Weeks" by Siraj Raval on Youtube
This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube
This is the Curriculum for "How to Learn Mathematics Fast" By Siraj Raval on Youtube
Machine Learning notebooks for refreshing concepts.
Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).
Classification of MI EEG signal using sparsity approach
Mutual Information functions for C and MATLAB
Code and guide through my customizable machine-learning pipeline for dry-EEG BCI data
Mother of All BCI Benchmarks
In this project, we use python, scikit-learn, tensorflow and MNE to build a classifier for predicting motor imagery from EEG data.
It includes OpenViBE scenarios for two-class motor imagery EEG data classification.
A basic implementation of multilayered neural network (deep learning) for motor imagery classification
It includes Motor Imagery EEG data for 15 subjects collected at BCI-HCI Labaratory at IIT Kharagpur.
Implementation of Deep Neural Networks in Keras and Tensorflow to classify motor imagery tasks using EEG data
submitted to Global SIP 2018
A comparison of different machine learning algorithms for binary classification of EEG signals elicited from motor imagery
Matlab scripts for implementing a mutual-information-based algorithm for independent component analysis. The algorithm works by iteratively rotating pairs of principle components until an optimum is found. The cost function is based on the summed negentropy of the discovered components, which is closely relative to the component mutual information.
mutualinformation analysis algorithms
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.