Difference between revisions of "Machine Learning Resources"

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* [https://github.com/keras-rl/keras-rl Keras-RL]
 
* [https://github.com/keras-rl/keras-rl Keras-RL]
 
* [https://github.com/combust/mleap mleap]
 
* [https://github.com/combust/mleap mleap]
 
+
* [https://github.com/mlflow/mlflow/blob/master/docs/source/models.rst MLflow models]
 
==Neural Network Interpretability==
 
==Neural Network Interpretability==
 
*[https://github.com/tensorflow/lucid Lucid on tensorflow]
 
*[https://github.com/tensorflow/lucid Lucid on tensorflow]

Revision as of 13:44, 10 July 2019

Key Frameworks:

Commonly used loss functions including pointwise, pairwise, and listwise losses. Commonly used ranking metrics like Mean Reciprocal Rank (MRR) and Normalized Discounted Cumulative Gain (NDCG). Multi-item (also known as groupwise) scoring functions. LambdaLoss implementation for direct ranking metric optimization. Unbiased Learning-to-Rank from biased feedback data.)

Neural Network Interpretability


Python Notebook Examples

Image Quality Assessment


Transfer Learning


Learning To Rank Articles