Difference between revisions of "Machine Learning Resources"

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* [https://towardsdatascience.com/introducing-tf-ranking-f94433c33ff Introduction to Tensorflow Ranking]
 
* [https://towardsdatascience.com/introducing-tf-ranking-f94433c33ff Introduction to Tensorflow Ranking]
 
* [https://medium.com/expedia-group-tech/real-time-serving-machine-learning-models-with-mleap-151b39dfc3d7 Mlleap usage]
 
* [https://medium.com/expedia-group-tech/real-time-serving-machine-learning-models-with-mleap-151b39dfc3d7 Mlleap usage]
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* [https://github.com/combust/mleap Converting Create & Export Spark Pipeline]

Revision as of 13:41, 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