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GPT-2 language model code and research from OpenAI
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VIP cheatsheets for Stanford's CS 229 Machine Learning course
A comprehensive repository covering papers, codes, datasets, tutorials, and applications for transfer learning, domain adaptation, and more.
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
Unsupervised text tokenizer for neural network-based text generation and natural language processing.
A Python library for outlier and anomaly detection, integrating classical and deep learning techniques.
A comprehensive collection of resources for anomaly detection, including books, papers, videos, and toolboxes.
Solutions and notes for the Machine Learning Specialization by Andrew NG on Coursera.
An open-source anomaly detection library with state-of-the-art algorithms and features like experiment management and edge inference.
A Python library of extension and helper modules for data analysis and machine learning.
A self-supervised learning framework for computer vision tasks with a focus on contrastive learning.
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
A library for training multilingual word embeddings, useful for NLP tasks across languages.
MUNIT is a deep learning-based method for multimodal unsupervised image-to-image translation, enabling vibe coders to create diverse and stylized images.
A versatile NLP toolkit for text mining and preprocessing, supporting tasks like sentiment analysis, entity extraction, and keyword summarization.
Official PyTorch implementation of U-GAT-IT, an unsupervised generative adversarial network for image-to-image translation.
Detects anomalies and drift in data with algorithms for outlier, adversarial, and concept-drift detection.
PyTorch implementation of SimCLR, a simple framework for contrastive learning of visual representations.
A framework for integrated Artificial Intelligence & Artificial General Intelligence (AGI)
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