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Hi there, I'm Alex 👋

Data Scientist, Machine Learning Engineer and Data Engineer developing solutions, accelerators and projects for DSML in various domains. Areas of specialisation include Geospatial DSML and analytics, graph theory, clustering, predictive modelling, CNNs, RNNs, with a focus on applying the Spark platform using Scala and Python. My experience includes data modelling, feature engineering, exploratory data analysis, root cause investigation across large and complex data sets in FinServ, HLS, Media & Entertainment and Telecom.


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Alex Taylor-Barreto Databricks's Projects

adb-essentials-demos icon adb-essentials-demos

Azure Databricks essentials demos used in our webinars: https://databricks.com/p/webinar/azure-databricks-essentials-series

adverse-drug-events icon adverse-drug-events

To ensure ongoing drug safety, pharma companies need to monitor and report adverse drug events post-market launch. This accelerator extracts, processes and analyzes adverse drug events from real-world text data using NLP

anomalib icon anomalib

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

auto-data-linkage icon auto-data-linkage

Low effort linking and easy de-duplication. Databricks ARC provides a simple, automated, lakehouse integrated entity resolution solution for intra and inter data linking.

car-classification icon car-classification

By applying transfer learning on pre-trained neural networks, we demonstrate how Databricks helps insurance companies kickstart their AI/Computer Vision journey towards claim assessment and damage estimation.

churn icon churn

Develop an understanding of how a customer lifetime should progress and examine where in that lifetime journey customers are likely to churn so you can effectively manage retention and reduce your churn rate.

cmv-commitee-rec-nlp icon cmv-commitee-rec-nlp

A Data Analytics Service (DAS) NLP solution for the Center for Minority Veterans council recommendations problem.

customer-lifetime-value icon customer-lifetime-value

Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases

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