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ProcessMiner™ Manufacturing Industry Case Studies

ProcessMiner™ Director of Science, Chitta Ranjan, shares his extensive research on data in the manufacturing industry.

LSTM Autoencoder for Extreme Rare Event Classification in Keras

LSTM Autoencoder for Extreme Rare Event Classification in Keras

Here we will learn the details of data preparation for LSTM models, and build an LSTM Autoencoder for rare-event classification. This post is a continuation of my previous post-Extreme Rare Event Classification using Autoencoders. In the previous post, we talked about the challenges in an extremely rare event data with less than 1% positively labeled data.

Estimating Non-Linear Correlation in R

Estimating Non-Linear Correlation in R

Correlation estimations are commonly used in various data mining applications. In my experience, nonlinear correlations are quite common in various processes. Due to this, nonlinear models, such as SVM, are employed for regression, classification, etc.

Sequence Embedding for Clustering and Classification

Sequence Embedding for Clustering and Classification

Here we will learn an approach to get vector embeddings for string sequences. These embeddings can be used for Clustering and Classification. Sequence modeling has been a challenge. This is because of the inherent un-structuredness of sequence data. Just like texts in Natural Language Processing (NLP), sequences are arbitrary strings.

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