Marcos Cedenilla - Portfolio

Recent Projects

Predicting Stock Market Trends

Data science project to forecast stock market assets.

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Full Data Science Project, Scientific Articles Retrieval

Created an infrastructure to process and store scientific articles using advanced technologies.

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NOAA Web Analysis

Creating a distributed ETL and TimescaleDB system orchestrated with Kubernetes to analyze NOAA data.

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Recent Articles

Predicting Stock Market Trends with Data Science: Part 4 — ARIMA Models, LSTM and Transformers

Published on September 17, 2024

"Predicting Stock Market Trends with Data Science: Part 4 — ARIMA Models, LSTM, and Transformers" delves into advanced prediction models...

Developing an ETL Pipeline for Massive NOAA Sensor Data: From Raw Files to Predictive Insights

Published on November 5, 2024

This article outlines the ETL pipeline of a NOAA analytics project, detailing how over 31 GB of climatic data are processed using Apache Spark and Kubernetes. It explains how raw sensor data is transformed into structured data for predictive analytics and visualizations, emphasizing scalability, reliability, and the integration of spatial metadata for geospatial queries.

Optimizing Geospatial and Time-Series Queries with TimescaleDB and PostGIS

Published on November 5, 2024

This article details the database architecture of a NOAA analytics project, focusing on using TimescaleDB and PostGIS on PostgreSQL to optimize geospatial and time-series queries. It covers Docker and Kubernetes configurations for deploying the database securely and efficiently within a cluster environment.