Gdynia

Hotel Nadmorski, Ejsmonda 2, Gdynia, Poland, 81-409

The training room is located just 3 kilometers from the PKP/PKS Station in Gdynia, making it easily accessible for participants traveling by train or bus. Additionally, it is only 400 meters away from the bus stop, facilitating access even for those using public transportation. It is equipped with necessary training tools such as a projector, screen, and flipchart, providing comfortable conditions for both participants and the trainer.

Gdańsk

Hotel Fahrenheit, Grodzka 19, Gdańsk, Poland, 80-841

The training room is located in the very heart of the picturesque Gdansk Old Town, making the surroundings not only inspiring but also exceptionally attractive for participants. Within close proximity, you can find the railway and bus stations, facilitating arrival for those traveling by both train and bus. Additionally, the airport and port are also within reach, making this location convenient for individuals coming from distant places, both domestically and internationally.

Subcategories (2)

Random Forest

Random Forest
AdaBoost

AdaBoost

Explore Our Courses

LightGBM for Machine Learning

 21 Hours
This instructor-led, live training in Trojmiasto (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 Trojmiasto (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 Trojmiasto (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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