PCA, Decision trees, Recurrent models, Probabilistic programming, VGG, Word2vec
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Clustering is a machine learning technique of finding similarities in the data point and grouping similar entities together. Clustering is often conducted at the stage of exploratory data analysis to better understand the dataset structure, or as a preliminary step for more complicated models.
To identify and match heterogeneous data from various sources in different formats.
To implement a highly-parallel complex algorithm with embedded RNN, CNN and DNN architectures for various types of media. Based on DTW path, Euclidian and cosine distances different metrics were defined. To get final results, bloom filters were applied.
A two-step parallel algorithm performing fast clusterization of given data with very high confidence score and capable to speed up data processing by a factor of 10.
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The technique to identify unusual patterns that do not conform to expected behavior
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