https://github.com/aliabd/history-of-interpretation
Saliency methods link a deep neural network's (DNN) prediction to the input features that most
influence that prediction. #Library
Saliency methods link a deep neural network's (DNN) prediction to the input features that most
influence that prediction. #Library
GitHub
aliabd/history-of-interpretation
TensorFlow implementation for SmoothGrad, Grad-CAM, Guided backprop, Integrated Gradients and other saliency techniques - aliabd/history-of-interpretation
https://github.com/fbdesignpro/sweetviz In-depth EDA (target analysis, comparison, feature analysis, correlation) #Library #Tools
example of use: http://cooltiming.com/SV/SWEETVIZ_REPORT_COMPARED.html
example of use: http://cooltiming.com/SV/SWEETVIZ_REPORT_COMPARED.html
GitHub
GitHub - fbdesignpro/sweetviz: Visualize and compare datasets, target values and associations, with one line of code.
Visualize and compare datasets, target values and associations, with one line of code. - fbdesignpro/sweetviz
https://github.com/jessevig/bertviz
BertViz is a tool for visualizing attention in the Transformer model, supporting most models from the transformers library (BERT, GPT-2, XLNet, RoBERTa, XLM, CTRL, MarianMT, etc.). #Library #Tools
BertViz is a tool for visualizing attention in the Transformer model, supporting most models from the transformers library (BERT, GPT-2, XLNet, RoBERTa, XLM, CTRL, MarianMT, etc.). #Library #Tools
GitHub
GitHub - jessevig/bertviz: BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.) - GitHub - jessevig/bertviz: BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
https://elastiknn.com/ Elasticsearch Plugin for Nearest Neighbor Search on dense vectors
#Tools #Library
#Tools #Library
Elastiknn
Home
Elasticsearch Plugin for Nearest Neighbor Search
https://github.com/yzhao062/pyod outlier/anomaly detection - many methods in one library #framework #library
GitHub
GitHub - yzhao062/pyod: A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques - yzhao062/pyod
https://faker.readthedocs.io/en/stable/index.html
https://sdv.dev/
https://gretel.ai/synthetics
Synthetic Data Generators! #Frameworks #Library
https://sdv.dev/
https://gretel.ai/synthetics
Synthetic Data Generators! #Frameworks #Library
sdv.dev
The Synthetic Data Vault. Put synthetic data to work!
The Synthetic Data Vault (SDV) enables end users to easily generate synthetic data for different data modalities, including single table, relational and time series data.
https://github.com/SeldonIO/alibi-detect Algorithms for outlier, adversarial and drift detection
https://github.com/SeldonIO/alibi Algorithms for explaining machine learning models
#Frameworks #library #anomaly #drift
https://github.com/SeldonIO/alibi Algorithms for explaining machine learning models
#Frameworks #library #anomaly #drift
GitHub
GitHub - SeldonIO/alibi-detect: Algorithms for outlier, adversarial and drift detection
Algorithms for outlier, adversarial and drift detection - SeldonIO/alibi-detect
NVidia: Traditional machine learning on GPU: various clustering, UMAP, TSNE, PCA, etc. #FYI #library
https://github.com/rapidsai/cuml
https://docs.rapids.ai/api/cuml/stable/
https://github.com/rapidsai/cuml
https://docs.rapids.ai/api/cuml/stable/
GitHub
GitHub - rapidsai/cuml: cuML - RAPIDS Machine Learning Library
cuML - RAPIDS Machine Learning Library. Contribute to rapidsai/cuml development by creating an account on GitHub.