Wrocław

NobleProg , Ludwika Rydygiera 2a/22, Wroclaw, Poland, 50-249

Classroom is located in the city center (right next to HP Park Plaza), just 10 minutes walk from the market square.

The entrance to the building is located from the Śrutowa street.

Wrocław, Ludwika Rydygiera 2a

Check our offer to rent rooms and rent computer equipment!

Parking

Near the classroom, the number of free parking spaces is limited, there is no paid parking zone (along Rydygiera, Śrutowa and Henryka Brodatego, Bolesława Drobnera streets).

Public transport
The nearest tram stops: Dubois, Pomorska
The nearest bus stops: Dubois

Jelenia Góra

Pałac Wojanów, Wojanów 8, Jelenia Góra, Poland, 58-508

Subcategories (2)

Random Forest

Random Forest
AdaBoost

AdaBoost

Explore Our Courses

LightGBM for Machine Learning

 21 Hours
This instructor-led, live training in dolnośląskie (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 dolnośląskie (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 dolnośląskie (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.
Read more...

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