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Skills

  • Analytics
  • Bootstrap
  • Cluster Analysis
  • Data Analysis
  • Data Processing
  • JavaScript
  • jQuery
  • MongoDB
  • MySQL
  • Node Js
  • PostgreSQL
  • Predictive Modeling
  • Python
  • Scrapy Framework
  • Web Development

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Services

  • Web Development

    $20/hr Starting at $30 Ongoing

    Dedicated Resource

    Web development using Nodejs and Express. Also implementing frontend JavaScript/Jquery solutions. Experience on developing web scraping applications.

    BootstrapJavaScriptjQueryMongoDBMySQL
  • Data Analysis and Predictions

    $20/hr Starting at $30 Ongoing

    Dedicated Resource

    ...

    AnalyticsCluster AnalysisData AnalysisData ProcessingPredictive Modeling

About

Critical thinking over Knowledge

I got my Master in Computer Engineering by implementing projects using multiple programming languages (C, C++, PHP, python, etc). I have experience with MySQL, PostgreSQL and MongoDB.

I have implemented a number of websites using both PHP frameworks and NodeJs.
1) Car rental and booking website: It was implemented using codeigniter and for the presentation i used bootstrap and made it responsive. The clients filled a form that was automatically send as an email to an administrator.
2) Journalism website for a team of bloggers: It was implemented using processwire.
3) News aggregator for online newspapers: The application consisted of two parts, one scraper and a website for presentation. It was implemented using nodejs, express and mongodb. Also for the scraper I used the cheerio package. The scraper requested the newest articles periodically, downloaded them and saved them on the database. In the website i implemented a search functionality by text in the title/contents, category, newspaper or time frame (and combinations of those).

After completing the courses of my second Master in Econophysics and Financial predictions i started delving in python and data analysis. I use pandas, numpy, scikit-learn and keras. I have also implemented some projects including neural networks, clustering and feature selection. I also use matplolib for presentation of results and data.

4) Prediction application for KINO: It was implemented using python, tensorflow/keras, pandas and essentially tries to predict KINO numbers using neural networks (both with LSTM and Perceptron).
5) Clustering application for election data: I used python with scikit-learn. I used different approaches to cluster the voters' answers and compare the results. I used distance methods, PCA, feature selection with PCA & LDA and clustering methods.