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A collection of pre-trained StyleGAN 2 models to download
StyleGAN-based predictor of children's faces from photos of theoretical parents.
Background Remover lets you Remove Background from images and video with a simple command line interface that is open source.
In this project, my team and I use Google's new BERT model to predict the S&P 500 using SEC 8-K filings
Решение с извлечение таблиц из pdf Camelot: PDF Table Extraction for Humans
Chainer implementation of Style-based Generator
A project for a class on neural networks where a deep-learning network was used to predict house prices.
Blind Face Restoration via Deep Multi-scale Component Dictionaries (ECCV 2020)
ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution (Third Region)
This work is used for pose estimation(yaw, pitch and roll) by Face landmarks(left eye, right eye, nose, left mouth, right mouth and chin)
A collection of deep learning frameworks ported to Keras for face analysis.
Face enhancer - Denoising Auto Encoder by Tensorflow and Keras and skimage
This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.
Fully-fledged Fundamental Analysis package capable of collecting 20 years of Company Profiles, Financial Statements, Ratios and Stock Data of 20.000+ companies.
Notebooks based on StyleGAN found in internet
Here is a series of face generators based on StyleGAN2
remove image background
Hair type predictions for better hair days
🥧 A tool for removing background from photos with neural networks 🥧
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Looking up a generative latent vectors from reference images.
This project is a linear regression modeling of kings county housing price prediction. The data set was provided by Flatiron School for Data Science Immersive course.
A deep learning approach to remove background & adding new background image
The estimation of real estate prices, are a useful and realistic approach for buyers and for local and fiscal authorities. It is of utmost importance to evaluate the current status of the market and predict its performance over the short term in order to make appropriate financial decisions. We will use two advanced modelling approaches Multi-Level Models and Artificial Neural Networks to model house prices. This approach is compared with the standard Hedonic Price Model in terms of accuracy in prediction, collecting the location information and their explanatory (interpretation) power. This project presents the development of a multi-layer artificial neural network-based models to support real estate investors and home developers in this critical task. The models utilize historical market performance data sets to train the artificial neural networks in order to predict unforeseen future performances. An application example is analyzed to demonstrate the model capabilities in analyzing and predicting the market performance. Given a set of values describing a house up for sale, a selling price is to be estimated based on the previous data. Before getting into predicting the sale-price of the house, exploratory data analysis will be performed to find out features having the highest weights in determining the same.
Working with neural networks for the first time attempting to predict accurately the price or number of rooms of various listings in Bucharest found on the website www.imobiliare.ro
OpenCV 4.2 with Python3.8 and video support (FFMPEG, GStreamer, gPhoto2) based on Alpine Linux 3.10
Remove image background and shadows
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.