Waldemar (Walt) Kołodziejczyk Email & Phone Number

Polska

Warszawa, Woj. Mazowieckie, Polska

1. Carrying out courses during Kodołamacz Data Science Bootcamp regarding: - classical ML supervised techniques (regression and classification), - ML unsupervised techniques (dimensionality reduction, clustering), - Text processing and analysis, - Deep Learning (image processing, NLP).2. Preparing and conducting "Machine Learning in Big Data" course during postgraduate studies "Big Data" at Warsaw University of Technology.3. Preparing and conducting… Show more 1. Carrying out courses during Kodołamacz Data Science Bootcamp regarding: - classical ML supervised techniques (regression and classification), - ML unsupervised techniques (dimensionality reduction, clustering), - Text processing and analysis, - Deep Learning (image processing, NLP).2. Preparing and conducting "Machine Learning in Big Data" course during postgraduate studies "Big Data" at Warsaw University of Technology.3. Preparing and conducting various ML/DS courses at StacjaIT. Show less

Warszawa, Woj. Mazowieckie, Polska

Preparing and conducting "Machine Learning in Big Data" course during postgraduate studies "Big Data"

Polska

Key responsibilities:-development of an intelligent Robotic Process Automation software,-implementing Computer Vision solutions,-development of Natural Language Processing tools,-development of pipeline for Optical Character Recognition,-creating data augmentation techniques and annotation verification tools.

Warsaw, Masovian District, Poland

Key responsibilities: - applying ML and AI algorithms for power engineering market, - time series forecasting, - data analysis, - power storage control (Reinforcement Learning),- building AutoML systems dedicated to time series forecasting,- research and development.

Master'S Degree, Computer Science, 5

The Faculty of Electronics and Information Technology Thesis title: "Real-time energy purchase optimization for a storage-integrated.

Bachelor Of Engineering - Be, Power Engineering, 5

Activities and Societies: Power Engineering Academic Study Group, High Efficient Engines Students Society "Stirling" The Faculty of Power.