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awesome-pretrained-stylegan2

A collection of pre-trained StyleGAN 2 models to download

babygan

StyleGAN-based predictor of children's faces from photos of theoretical parents.

backgroundremover

Background Remover lets you Remove Background from images and video with a simple command line interface that is open source.

bert-stock-prediction-using-nlp

In this project, my team and I use Google's new BERT model to predict the S&P 500 using SEC 8-K filings

camelot

Решение с извлечение таблиц из pdf Camelot: PDF Table Extraction for Humans

chainer-stylegan

Chainer implementation of Style-based Generator

deep_learning_real_estate_demo

A project for a class on neural networks where a deep-learning network was used to predict house prices.

dfdnet

Blind Face Restoration via Deep Multi-scale Component Dictionaries (ECCV 2020)

esrgan

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution (Third Region)

face-yaw-roll-pitch-from-pose-estimation-using-opencv

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)

face_toolbox_keras

A collection of deep learning frameworks ported to Keras for face analysis.

fc

Face enhancer‏ - Denoising Auto Encoder by Tensorflow and Keras and skimage

financedatabase

This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

fundamentalanalysis

Fully-fledged Fundamental Analysis package capable of collecting 20 years of Company Profiles, Financial Statements, Ratios and Stock Data of 20.000+ companies.

gans

Notebooks based on StyleGAN found in internet

generators-with-stylegan2

Here is a series of face generators based on StyleGAN2

hair

remove image background

hair-cam

Hair type predictions for better hair days

home_automation

image-background-remove-tool

🥧 A tool for removing background from photos with neural networks 🥧

image-segmentation-keras

Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

image-super-resolution

🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

inverse-style-gan

Looking up a generative latent vectors from reference images.

king_county_housing_price_prediction

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.

kings-county-housing-prediction-model

modnet-bgremover

A deep learning approach to remove background & adding new background image

multi-layer-artificial-neural-network-for-estimating-real-estate-prices

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.

neuralnetworkrealestate

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-video-minimal

OpenCV 4.2 with Python3.8 and video support (FFMPEG, GStreamer, gPhoto2) based on Alpine Linux 3.10

opencv_imagebackgroundremoval

Remove image background and shadows