Block or Report
Block or report roebius
Contact GitHub support about this user’s behavior. Learn more about reporting abuse.
Report abuseStars
Language
Sort by: Recently starred
Hybrid Quantum-Classical Machine Learning in TensorFlow
A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.
ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
A scrapy script for scraping FAQs from different sites
A guide/tutorial for running Scrapy with a serverless paradigm
An AWS CDK SSM Parameter Construct
An AWS Image Builder pipeline built with AWS CDK
This is intended to be a repo containing all of the official AWS Serverless architecture patterns built with CDK for developers to use. All patterns come in Typescript and Python with the exported …
Multilingual Sentence & Image Embeddings with BERT
A tool for extracting plain text from Wikipedia dumps
🚀100 Times Faster Natural Language Processing in Python - iPython notebook
A Pythonic wrapper for the Wikipedia API
A python package to convert numbers in word form to the traditional digit (numeric) form
Advanced NLP Workshop: word-sense disambiguation with RoBERTa and text summarization with BART (Machine Learning Milan)
Understanding COVID-19 through Italian excess deaths analysis
Python script to download all Springer books released for free during the 2020 COVID-19 quarantine
ml algorithm that pulls funny music videos from youtube
Different implementations of "Weighted Prediction Error" for speech dereverberation
speech enhancement using DNN: [1] Xu, Y., Du, J., Dai, L.R. and Lee, C.H., 2015. A regression approach to speech enhancement based on deep neural networks. IEEE/ACM Transactions on Audio, Speech an…
Code and audio files associated with the paper "Speech Enhancement with Variance Constrained Autoencoders" presented at Interspeech 2019
The state-of-art time domain network for speech separation, and it performs well on speech enhancement and music separation
Improved speech enhancement with the Wave-U-Net, a deep convolutional neural network architecture for audio source separation, implemented for the task of speech enhancement in the time-domain.