A module implementing custom literal suffixes using pure Python. custom-literals mimics C++’s user-defined literals (UDLs) by defining literal suffixes that can be accessed as attributes of literal values, such as numeric constants, string literals and more. (c) RocketRace 2022-present. See LICENSE file for more. See the examples/ directory for more. Function decorator syntax: from custom_literals import literal from datetime import timedelta @literal(float, int, name=”s”) def seconds(self): return timedelta(seconds=self) @

Predicts the likelihood of Polycystic Ovary Syndrome based on patient attributes and symptoms using Logistic Regression. Clone the Repository git clone https://github.com/smv5467/pcos-prediction Add Dependencies with Poetry If you don’t have poetry install with: curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python – poetry install Download Data Retrieve data from Kaggle: https://www.kaggle.com/prasoonkottarathil/polycystic-ovary-syndrome-pcosDownload PCOS_data_without_infertility.xlsxOpen excel file and save as a CSV file under the same name Run program poetry run python pcos_predictor.py GitHub View Github    

Heterogeneous Star Graph Attention Network for Product Attributes Prediction This repository contains the official PyTorch implementation for ADVIE Paper “Heterogeneous Star Graph Attention Network for Product Attributes Prediction“.We also present the Alibaba Custermers Interaction Dataset used in this paper. Citation If you find this code or dataset is helpful, please kindly consider citing the following papers: Zhao, Xuejiao, et al. “Heterogeneous star graph attention network for product attributes prediction.” Advanced Engineering Informatics. 51, 101447. 2022.

PyTorch implementation for the paper: FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning Chenxu Zhang,Yifan Zhao,Yifei Huang,Ming Zeng,Saifeng Ni,Madhukar Budagavi,Xiaohu Guo ICCV 2021 Run demo on Google Colab Requirements conda create -n audio_face conda activate audio_face sudo apt-get install ffmpeg pip install -r requirements.txt you may add opencv by conda. Citation