Rzeszów

RISE, Plac Wolności 13, Rzeszów, Poland, 35-073

The training room is located in the very heart of Rzeszow, making it easily accessible for participants. In the immediate vicinity, there are major public transportation hubs, such as city buses (MPK), railways (PKP), and long-distance buses (PKS), facilitating access from various parts of the city and beyond. Additionally, there is an underground parking garage at the Center Park gallery nearby, providing convenient parking for those using their own vehicles.

Głogów Małopolski

NobleProg , Strefowa 1, Głogów Małopolski, Poland, 36-060

The training room is located just 10 km southwest of Rzeszow, directly on the Rzeszow-Radom route, providing easy access from both cities. Additionally, its proximity to the A4 motorway and Jasionka airport facilitates transportation for both car travelers and those utilizing air transport.

Subcategories (2)

Random Forest

Random Forest
AdaBoost

AdaBoost

Explore Our Courses

LightGBM for Machine Learning

 21 Hours
This instructor-led, live training in podkarpackie (online or onsite) is aimed at beginner to intermediate-level developers and data scientists who wish to learn the basics of LightGBM and explore advanced techniques. By the end of this training, participants will be able to:
  • Install and configure LightGBM.
  • Understand the theory behind gradient boosting and decision tree algorithms
  • Use LightGBM for basic and advanced machine learning tasks.
  • Implement advanced techniques such as feature engineering, hyperparameter tuning, and model interpretation.
  • Integrate LightGBM with other machine learning frameworks.
  • Troubleshoot common issues in LightGBM.
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AdaBoost Python for Machine Learning

 14 Hours
This instructor-led, live training in podkarpackie (online or onsite) is aimed at data scientists and software engineers who wish to use AdaBoost to build boosting algorithms for machine learning with Python. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building machine learning models with AdaBoost.
  • Understand the ensemble learning approach and how to implement adaptive boosting.
  • Learn how to build AdaBoost models to boost machine learning algorithms in Python.
  • Use hyperparameter tuning to increase the accuracy and performance of AdaBoost models.
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Machine Learning with Random Forest

 14 Hours
This instructor-led, live training in podkarpackie (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building machine learning models with Random forest.
  • Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
  • Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
  • Evaluate and optimize machine learning model performance by tuning the hyperparameters.
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