Mayur (mayurnewase)

mayurnewase

Geek Repo

Location:Earth C-42

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Organizations
superset-collab

Mayur's repositories

AutoBidder-for-VastAI-instances

Bid automatically on gpu instances for cheapest prices

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kaggle-manager

Manage Kaggle Submitions

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Quora-Bert

BERT modified for toxic classification

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ANPR

licence plate detection and recognition

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Background-Matting

Background Matting: The World is Your Green Screen

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BentoML

Model Serving Made Easy

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darknet

YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

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espnet

End-to-End Speech Processing Toolkit

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Face-Recognition

One Shot Learning using siamese network

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jukebox

Code for "Jukebox: A Generative Model for Music"

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nlp

🤗nlp – Datasets and evaluation metrics for Natural Language Processing in NumPy, Pandas, PyTorch and TensorFlow

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onnxruntime

ONNX Runtime: cross-platform, high performance scoring engine for ML models

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python-telegram-bot

We have made you a wrapper you can't refuse

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redis

Redis as a private Docker service on Render

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spaCy

💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

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svoice

We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.

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Toxic-Comment-Classifier

Filter toxicity using machine learning

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twitter-scraper

Scrape the Twitter Frontend API without authentication.

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Unique-Identity-Project-

Engineering semester 5th project for giving unique identity to customers.

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vidgear

High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features :sparkles:

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WaveRNN

WaveRNN Vocoder + TTS

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