Category Archives: Deep Learning

Simulating A/B Test with Counterfactual and Machine Learning Regression Model

Performing A/B test is costly. It takes time and resource.AB testing is a way trying multiple versions of something to find out which works best based on some metric. it’s also called Randomized Controlled Test (RCT). There are many application … Continue reading

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Machinery Fault Detection with Vibration Data Anomaly Detection using Variational Auto Encoder.

Auto Encoder is a unsupervised Deep Learning model. Data is encoded to a lower dimensional latent space using an encoder network. The decoder decodes the latent space data trying to reconstruct the original data. With Variational Auto Encoder (VAE), the … Continue reading

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Tabular Data Column Semantic Type Identification with Contrastive Deep Learning

When data is aggregated from various source in a dynamic environment where the data format might change without any notice, identifying semantic type of columns in data is a challenging problem. In this post the problem semantic type identification of … Continue reading

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Discovering Subject Matter Experts from Email Communication Data using Graph Convolution Network.

Deep Learning model architecture aligns with a specific structure of the data e.g RNN or LSTM for linear data like text, CNN for grid data like image. The structure of the data in these cases are specialized kind graph structure. … Continue reading

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Remedial Action Recommendation with Machine Learning and Genetic Algorithm

Prescriptive analytic sits at the top of a three tier analytic pyramid. The bottom layers are descriptive and predictive analytic. Prescriptive analytic entails action recommendations based on the results of descriptive and predictive analytic, which if executed will have have … Continue reading

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Deep Learning based Anomaly Detection for Data with Temporal and Spatial Correlation

Anomaly detection for data with both temporal ans spatial correlation is a complex problem and most of the solutions are based on deep learning.This post contains high level overview of various deep learning based anomaly detection solutions for spatio temporal … Continue reading

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Duplicate Data Detection with Neural Network and Contrastive Learning

Duplicate data is a ubiquitous problem in the data world. It often appears when data from different silos are consolidated. It could be an issue in an analytic project based on data aggregated from various sources. The training data for … Continue reading

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Causal Inference with Deep Learning using Manufacturing Supply Chain Optimization as an Example

Machine Learning has been very successful using observational data to build models for predictions, but does not go far enough for causal inference. We humans use cause and effect to learn about the world. In causal inference statistical tools are … Continue reading

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Predicting Individual Viral Infection using Contact Data with LSTM Neural Network

With Covid-19 ravaging the world, lot of people are exploring ways AI and ML can help in combating the virus spread and infection. Virus like Covid-19  is a complex socio economic and public health problem and the solutions cut across … Continue reading

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Semantic Search with Pre Trained Neural Transformer Model using Document, Sentence and Token Level Embedding

Some time ago I  worked on an enterprise search project, where we were tasked to improve the performance of an enterprise Solr search deployment. We recommended various improvements based on classic NLP techniques. One of the items on the agenda … Continue reading

Posted in AI, Deep Learning, elastic search, Machine Learning, NLP, Python, PyTorch, Search | Tagged , , , , , , , , | 5 Comments