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Name: JUDITH NJOKU
Type: User
Bio: I am a self taught Front-end developer and Machine learning engineer, veraciously seeking to learn more
Location: Nigeria
Blog: judithnjoku.com
Name: JUDITH NJOKU
Type: User
Bio: I am a self taught Front-end developer and Machine learning engineer, veraciously seeking to learn more
Location: Nigeria
Blog: judithnjoku.com
The hybrid model combining stacked denoising autoencoder with matrix factorization is applied, to predict the customer purchase behavior in the future month according to the purchase history and user information in the Santander dataset.
Predict valence and arousal from video data. Separate training of CNN and RNN. Feed RNN with simple feature vectors extracted from frames. Feature extraction is done by a simple CNN model.
the python codes of paper "Communication-oriented Autoencoders - where Shannon meets Wiener"
Digital Communication using deep learning
A simple implementation of the autoencoder for wireless communication using Tensorflow 2
Course Files for Complete Python 3 Bootcamp Course on Udemy
Quick and dirty example of the application of convolutional autoencoders in Keras/Tensorflow
Spring 2017 Deep Reinforcement Learning Final Project
Bachelor Thesis
This is the COST2100 channel model, a MATLAB implementation of a spatially consistent radio channel model for MIMO and Massive MIMO communication. Originally developed within COST 2100 (http://www.cost2100.org/) and then further extended in COST IC 1004 (http://www.ic1004.org/) and COST CA15104 IRACON (http://www.iracon.org/)
Machine learning-Stanford University
This is the code that generates the figures in the paper titled "Covariance Matrix Estimation for Massive MIMO" authored by Karthik Upadhya and Sergiy A. Vorobyov and published in IEEE Signal Processing Letters, vol. 25, no. 4, pp. 546-550, April 2018.
covid19
This is a repository for the code developed to produce the results in the paper titled "Cognitive radio network with coordinated multipoint joint transmission" (http://onlinelibrary.wiley.com/doi/10.1002/dac.3310/abstract)
Determine the modulation type of a received signal under AWGN channel in a cognitive radio (CR) system.
EXPLORING THE IRIS DATA SET
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
Model for Cognitive Radio Ad hoc Network Simulations in OMNeT++
🦍 Stanford CS236 : Deep Generative Models
State of charge and state of health estimation of Li-ion battery
code for "DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification"
AI-based User Adaptive Interaction Laboratory
Data Cleaning In Python and Julia with Practical Examples
Data Scraping and Cleaning workshop on Python.
Machine learning datasets used in tutorials on MachineLearningMastery.com
Simulation code for decentralized baseband processing (DBP) in massive MIMO systems
Dynamic channel allocation in cellular networks by reinforcement learning
aims to develop an IDS (Intrusion Detection System) using Autoencoder. For this, we normalized the data sets from the Kyoto 2006+ dataset to fit Autoencoder
Continuous control with deep reinforcement learning - Deep Deterministic Policy Gradient (DDPG) algorithm implemented in OpenAI Gym environments
Simple MATLAB simulator for decentralized feedforward equalization in massive MU-MIMO systems
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.