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Word-Embeddings-and-Document-Vectors
An evaluation of word-embeddings for classificationBow-to-Bert
Evolution of word vectors from long, sparse, and 1-hot to short, dense, and context sensitiveConcept-Drift-and-Model-Decay
Evaluating model decay as the underlying concepts for classification evolveELK-Stack-with-Vagrant-and-Ansible
Building an ELK stack with Vagrant and AnsibleNonlinear-Classification-with-Logistic-Regression
Kafka-Streams-Catching-Data-in-the-Act
An implementation of Kafka Streamscontext-aware-word-vectors
Context aware word vectorsEvaluating-Document-Transformations-for-Clustering-Text
Serving-Flask-on-Docker
Dockerizing a Flask web application behind gunicorn and NginxMulticlass-classification-with-word-bags-and-word-strings
A-Flask-full-of-WSGI
Serving up python web applications has never been easier with the suite of WSGI servers at our disposal. Both uWSGI and gunicorn behind Nginx are excellent performers for serving up a Flask app…Clustering-text-with-tranformed-document-vectors
Clustering Text with Transformed Document Vectorsword-bags-vs-word-sequences-for-text-classification
Evaluating sequence respecting approaches like LSTM against traditional bag-of-words approaches for textVirtual-Clusters-with-Vagrant-Virtualbox
Virtual Clusters with Vagrant & VirtualboxReconciling-Data-Shapes-and-Parameter-Counts-in-Keras
Deriving formulae for parameter counts when using convolutional layersChoosing-the-Optimal-Number-of-Clusters-for-K-Means
Detecting the optimal number of clusters to use with K-meansFracking-Features-in-Machine-Learning
Detecting data evolution and the need for new classesELK-Clusters-on-AWS-with-Ansible
Building ELK Clusters on AWS with Ansiblecomputing-on-coupled-data-streams-with-Beam
Coupled data streams need to be analyzed together ensuring simultaneity of events across the participant streamsAttention-as-Dynamic-Tf-Idf-for-Deep-Learning
Implementing attention to recover task specific weighting of wordsLove Open Source and this site? Check out how you can help us