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backgroundremoval

Small Streamlit app to help with background removal on images

bank_marketing_database

In this project we design a bank marketing database

berea_pnm

Investigation of the Berea sandstone pore network modeling

cpp-challenges

css-layout

deep-nilmtk-v1

Deep-NILMtk is an open source package designed specifically for deep models applied to solve NILM. It implements the general NILM pipeline independently of the deep learning backend. In its current version the toolkit considers two of the most popular deep learning pipelines. The training and testing phases are fully compatible with NILMtk. Several

fast-stable-diffusion

fast-stable-diffusion, +25-50% speed increase + memory efficient + DreamBooth

fastapi_msal

A FastAPI Plug-In to support authentication authorization using the Microsoft Authentication Library (MSAL)

flask-website

flexbox

haystack

:mag: Haystack is an open source NLP framework that leverages pre-trained Transformer models. It enables developers to quickly implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications.

health_e

machinevaluation

Enterprise Valuations Based on Machine Learned Associations. WARNING: Experimental Research Project in Beta. Do NOT use for investment decisions!

nilm_metadata

A schema for modelling meters, measurements, appliances, buildings etc

nilmtk

Non-Intrusive Load Monitoring Toolkit (nilmtk)

online_retail_data

Here we analyse a kaggle dataset of online retail transaction data set of two years.

pattern

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

petrography2sem

robofriends

smart-brain

smart-brain-api

speechtopictogram

stable-diffusion-videos

Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts

startup-landing-page

thanks-givers

tldr-this

Cohere Thanksgiving Hackathon

tutorials

tweet

Generate Tweet texts using OpenAI's GPT-3 based Davinci model

wood_defect_detection