Michał Żarnecki Portfolio

I'm a programmer and lecturer. My work is related to programming in Python/PHP/JavaScript and designing systems and solutions related to AI/machine learning, data mining, big data and natural language processing.

Tag: ScikitLearn

E-learning course: Machine learning – how to use the potential of data to get better results and make smart decisions

Posted on 3 January 2024  in lectures

Course scenario:

  1. Definition and applications of machine learning
    • Data deluge and the definition of machine learning
    • Machine learning examples and related fields of knowledge
    • Types of machine learning
  2. Machine learning tools used in the course
    • Programs used in the course
    • Orange Data Mining
    • Jupyter Lab
  3. Supervised machine learning
    • Machine learning process
    • Data collection, labeling and analysis
    • Feature engineering and division into training and testing sets
    • Model training and evaluation
    • Model export, corrective actions
    • Regression example
    • Classification example
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Tag: ScikitLearn

Machine Learning – topic modelling for german companies description

Posted on 24 February 2019  in projects

Machine learning model and web service predicting company industry codes based on description.

Responsibilities:

  • Implement machine learning model classyfing text into over 100 classes
  • German text preprocessing and normalization
  • Evaluation and, upgrading model parameters
  • Implement web service for real time prediction

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Tag: ScikitLearn

System to collect networking and finance data about German companies

Posted on 1 July 2017  in projects

Pictures from moneyhouse.de

 

Web application to collect networking and finance data about German companies.

Responsibilities:

  • Implementing data mining tools and parsers using deterministic algorithms and deep learning models
  • creating fast and efficient search engine
  • carrying out integration with external platforms, APIs, web-services
  • working with Selenium, automation of acceptance, integration, functional and unit tests, TDD
  • conducting data analysis using Python, R
  • server environment setup and configuration

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