Semi Supervised Learning Python Packages

alibi-detect

Algorithms for outlier, adversarial and drift detection

adbench

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

otx

OpenVINO™ Training Extensions: Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

tape-proteins

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

accelbrainbeat

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

rul-datasets

A collection of datasets for RUL estimation as Lightning Data Modules.

bio-embeddings-tape-proteins

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

pysummarization

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

semilearn

Unfied Semi-Supervised Learning Benchmark

susi

SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)

pydbm

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

pytorch-partial-tagger

Sequence Tagger for Partially Annotated Dataset in PyTorch

accel-brain-base

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

visagesnap

Easy-to-Use library to recognize faces, train the model, provide predictions

ts3l

A PyTorch Lightning-based library for self- and semi-supervised learning on tabular data.

disc

A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

hypergbm

A full pipeline AutoML tool for tabular data

torchwisdom

High level API for training deep learning model in PyTorch

lamda-ssl

30 Semi-Supervised Learning Algorithms

ssl-dnx

TFG - Semisupervised learning and instance selection methods

pyqlearning

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

keras-unsupervised

Keras framework for unsupervised learning

semisupervisedlearningdnx

TFG - Semisupervised learning and instance selection methods

is-dnx

TFG - Semisupervised learning and instance selection methods