Difference between revisions of "Machine Learning Resources"

From Wiki2
Jump to navigation Jump to search
 
(14 intermediate revisions by the same user not shown)
Line 1: Line 1:
 
Key Frameworks:
 
Key Frameworks:
 
* [https://www.tensorflow.org/beta Tensorflow (beta 2.0)]
 
* [https://www.tensorflow.org/beta Tensorflow (beta 2.0)]
* [https://pytorch.org/docs/stable/torch.html Pytorch]
 
* [https://scikit-learn.org/stable/ Scikit-learn]
 
 
* [https://www.tensorflow.org/probability Tensorflow Probability]
 
* [https://www.tensorflow.org/probability Tensorflow Probability]
 
* [https://github.com/tensorflow/ranking Tensorflow Rank] (TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform. It contains the following components:
 
* [https://github.com/tensorflow/ranking Tensorflow Rank] (TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform. It contains the following components:
Line 11: Line 9:
 
Unbiased Learning-to-Rank from biased feedback data.)
 
Unbiased Learning-to-Rank from biased feedback data.)
  
 +
* [https://pytorch.org/docs/stable/torch.html Pytorch]
 +
* [https://scikit-learn.org/stable/ Scikit-learn]
 +
* [https://scikit-image.org/ Scikit-Image]
 
* [https://docs.databricks.com/applications/deep-learning/index.html Deep learning Databricks]
 
* [https://docs.databricks.com/applications/deep-learning/index.html Deep learning Databricks]
 
+
* [https://github.com/Microsoft/gated-graph-neural-network-samples Gated Graph Neural Networks Microsoft]
 +
* [https://autokeras.com/ AutoKeras]
 +
* [https://github.com/keras-rl/keras-rl Keras-RL]
 +
* [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]
Line 26: Line 31:
 
==Transfer Learning==
 
==Transfer Learning==
 
* [https://github.com/WillKoehrsen/pytorch_challenge/blob/master/Transfer%20Learning%20in%20PyTorch.ipynb PyTorch image classification using VGG-16]
 
* [https://github.com/WillKoehrsen/pytorch_challenge/blob/master/Transfer%20Learning%20in%20PyTorch.ipynb PyTorch image classification using VGG-16]
 +
 +
 +
==Object Recognition In Images==
 +
* [https://github.com/OlafenwaMoses/ImageAI Image AI] ()
 +
* [https://towardsdatascience.com/object-detection-and-tracking-in-pytorch-b3cf1a696a98 Object detection PyTorch]
 +
* [https://github.com/ayooshkathuria/pytorch-yolo-v3 Yolo_v3 Pytorch Implementation]
 +
 +
==Articles==
 +
* [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://github.com/combust/mleap Converting Create & Export Spark Pipeline]
 +
* [https://medium.com/airbnb-engineering/learning-market-dynamics-for-optimal-pricing-97cffbcc53e3 ML & Pricing Dynamics of Homes]
 +
* [https://medium.com/airbnb-engineering/listing-embeddings-for-similar-listing-recommendations-and-real-time-personalization-in-search-601172f7603e List embeddings for recommendation & real time personalisation in search ranking]
 +
* [https://eng.lyft.com/empowering-personalized-marketing-with-machine-learning-fd36e6bdeca6 ML applications in personalised marketing]

Latest revision as of 08:29, 14 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


Object Recognition In Images

Articles