How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
PyTorch implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences"
An interactive lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The the lab content is based on Python, IPython Notebook, and PyTorch.
The main features of gitihubi/deepai are: Financial NLP, Accounting Analytics, Anomaly Detection.
Open-source alternatives to gitihubi/deepai include: byungjae89/mahalanobisad-pytorch. byungjae89/spade-pytorch — PyTorch implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences". charleshoffmancpa/charleshoffmancpa.github.io. cqylunlun/glass. dongyuanxin/news-emotion — 挑战杯项目：金融文本情感分析模型 || Challenge Cup Project: Financial Text Emotion Analysis Model - 金融领域短文本情感分析 - 配置要求：python 3.x. agdgovsg/ml-coa-charging.