HROlive / Applications-of-AI-for-Anomaly-Detection

Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.

Date Created 2023-03-01 (2 years ago)

Commits 25 (last one 5 months ago)

Stargazers 45 (1 this week)

Watchers 1 (0 this week)

Forks 23

License unknown

Ranking

RepositoryStats indexes 641,700 repositories, of these HROlive/Applications-of-AI-for-Anomaly-Detection is ranked #524,814 (18th percentile) for total stargazers, and #563,745 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #14,407/19,417.

HROlive/Applications-of-AI-for-Anomaly-Detection is also tagged with popular topics, for these it's ranked: python (#20,466/23677), deep-learning (#7,696/8886), machine-learning (#7,349/8491), tensorflow (#2,114/2313), keras (#738/812), pandas (#537/612), generative-adversarial-network (#336/382), anomaly-detection (#295/358), notebook (#263/291)

All Topics

keras pandas python rapids xgboost notebook nvidia-gpu tensorflow autoencoders deep-learning machine-learning anomaly-detection generative-adversarial-network

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updated: 2025-04-20 @ 07:01pm, id: 608068384 / R_kgDOJD5jIA