100-Days-Of-ML-Code中文版
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Updated
Feb 22, 2022 - Jupyter Notebook
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100-Days-Of-ML-Code中文版
VIP cheatsheets for Stanford's CS 229 Machine Learning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
Anomaly detection related books, papers, videos, and toolboxes
A library of extension and helper modules for Python's data analysis and machine learning libraries.
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
The standard package for data-centric AI and machine learning with label errors, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.
A framework for integrated Artificial Intelligence & Artificial General Intelligence (AGI)
A curated list of pretrained sentence and word embedding models
A curated list of community detection research papers with implementations.
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
Unsupervised Learning for Image Registration
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
Is there a way to stabilise the results of the algorithm spot the diff drift detection?
In each run with same configuration and data the results of diff and p values are different.
Composable GAN framework with api and user interface
(CVPR'20 Oral) Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
an open-source implementation of sequence-to-sequence based speech processing engine
A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).
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For the autoencoder in pyod, how do I adjust the learning rate?