Training LightGBM in machine learning
Practical information about training
- CATEGORY: Technologies
- SUBCATEGORY: AI
- TRAINING CODE: IT-AI-129
- DURATION: 3 days
- PRICE INFORMATION from: 3750 PLN net
- LANGUAGE OF TRAINING: polish
- FORM OF IMPLEMENTATION: stationary, online
Training description
The training deepens the knowledge of using the LightGBM framework in advanced machine learning projects. Participants will learn techniques for optimizing and tuning gradient boosting models. The program combines theory with practical workshops, allowing participants to understand the mechanisms of the algorithm and use it effectively in real-world applications.
Participant profile
- Data Scientists working with gradient boosting models
- ML engineers optimizing model performance
- Data analysts in predictive projects
- Machine learning specialists
- ML systems programmers
- Researchers involved in predictive modeling
- Data analysis experts
- Algorithm optimization specialists
Agenda
- LightGBM Basics
- Architecture of the framework
- Comparison with other solutions
- Configuring the environment
- Data preparation
- Optimization of models
- Selection of hyperparameters
- Regularization techniques
- Categorical data handling
- Learning strategies
- Advanced functionalities
- Distributed learning
- Handling large data sets
- Custom target functions
- Early stopping
- Implementation and monitoring
- Serialization of models
- Integration with production systems
- Performance monitoring
- Model updates
Benefits
The participant will develop the ability to effectively use LightGBM in ML projects. Will learn to optimize model performance through advanced parameter tuning techniques. Will learn methods to effectively handle large data sets in the learning process. Will gain knowledge of implementing custom objective functions and metrics. Will be able to implement LightGBM models in a production environment. Will gain the ability to monitor and maintain models in real-time. Will develop the ability to debug and troubleshoot models. Will learn to select optimal learning strategies for different use cases.
Required preparation of participants
- Practical knowledge of machine learning
- Experience in working with tree models
- Familiarity with Python and data analysis libraries
- Fundamentals of numerical optimization
Issues
- LightGBM architecture
- Optimization of hyperparameters
- Regularization techniques
- Distributed learning
- Custom target functions
- Categorical data handling
- Early stopping
- Serialization of models
- Performance monitoring
- Learning strategies
- Debugging models
- Production updates
Do you have any questions?
Feel free to contact us.
Anna Polak
+48 600 010 440
anna.polak@eitt.pl
31 Ząbkowska Street 03-736 Warsaw
Forms of training delivery
Stationary training
- Training at the customer's premises or at a designated location
- Training room equipped with the necessary equipment
- Training materials in electronic form
- Coffee breaks and lunch
- Direct interaction with the trainer
- Networking in a group
- Workshop exercises in teams
Remote training
- Virtual training environment
- Electronic materials
- Interactive online exercises
- Breakout rooms for group work
- Technical support during the training
- Recordings of the session (optional)
Possibility of funding
The training can be financed with public funds under:
- National Training Fund (KFS)
- Development Services Base (BUR)
- EU projects implemented by PARP
- HR Academy Program (PARP)
- Regional operational programs
If you are interested in funding, our team will help you prepare the required documentation.
HAVE A QUESTION?
Contact us for more information about our training, programs and cooperation. We will be happy to answer all your inquiries!
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Do you have any questions?
Feel free to contact us.
Anna Polak
+48 600 010 440
anna.polak@eitt.pl
31 Ząbkowska Street 03-736 Warsaw
FAQ - Frequently Asked Questions
- One-pager invitation with deadlines
- Project kick-off
- Strategic leadership and thinking
- Communication and Cooperation. Conflict management
- Motivating, engaging and difficult decisions in business
- Managing Change and Innovation. Leadership in crisis
- Building the organization of the future
- Best practices workshop - retrospective; creating a coherent program for middle and lower management levels























