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gpsyrou/README.md

👋 Hi there

Thank you for visiting my profile. My name is George and I am a Data Scientist currently working and living in London, UK.

💻 📚 Interests

My passion is around topics related to statistics, computer science and the intersection of these two fields. I enjoy working with different types of algorithms, from classification & regression, to clustering and graph/network models, and find ways to use my data analytics experience to investigate and solve real world problems.

Motto: "Life is short, use Python"

🔧 Tech Stack

Python R SQL PostgreSQL C  C Azure Flask Shell cript Jupyter Notebook Amazon Web Services

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  1. tube-virality tube-virality Public

    Develop an API to retrieve statistics and information around Youtube trending videos. Perform descriptive statistics analysis, and build models able to project the likelihood of a trending video to…

    Python 10 2

  2. Text_Analysis_of_Consumer_Reviews Text_Analysis_of_Consumer_Reviews Public

    Natural Language Processing (NLP) and analysis on reviews about delivery companies in the UK based on reviews extracted from the Trustpilot website

    Python 2 2

  3. Twitter_Sentiment_Analysis Twitter_Sentiment_Analysis Public

    Exploration of the Twitter API and sentiment & topic analysis on tweets relevant to COVID-19

    Python 6 6

  4. Categorization_Consumer_Complaints Categorization_Consumer_Complaints Public

    Use of XGboost and Multinomial Naive Bayes, along with AWS SageMaker, to perform automatic text classification of consumer complaints to their respective categories

    Python 2

  5. Binary_Classification_of_Bank_Marketing_Campaigns Binary_Classification_of_Bank_Marketing_Campaigns Public

    Exploratory data analysis (EDA) and development of classification algorithms (Logistic Regression, Random Forest) to predict clients that are most likely to subscribe to a bank's product, as a resu…

    Jupyter Notebook

  6. Vaccines_Trade_Network Vaccines_Trade_Network Public

    Implementation of ARIMA and Holt-Winters Exponential Smoothing models for the analysis of the global network of human vaccines for the period 2010-2019

    Python