Training Algebra in machine learning
Practical information about training
- CATEGORY: Technologies
- SUBCATEGORY: AI
- TRAINING CODE: IT-AI-147
- DURATION: 2 days
- PRICE INFORMATION from: 2450 PLN net
- LANGUAGE OF TRAINING: polish
- FORM OF IMPLEMENTATION: stationary, online
Training description
Advanced training exploring the mathematical foundations of machine learning, with a focus on linear algebra and its applications. The program combines mathematical theory with the practical use of algebraic concepts in the implementation of ML algorithms. The classes are conducted in the form of interactive workshops, where abstract mathematical concepts are illustrated with concrete examples from the field of machine learning, and theory is immediately verified through implementations in Python.
Participant profile
- Machine learning engineers looking to deepen their mathematical knowledge
- Data scientists in need of a solid algebraic foundation
- ML programmers interested in optimizing algorithms
- Researchers involved in advanced ML techniques
- Data analysts developing theoretical skills
- Mathematicians moving into the ML field
- PhD students specializing in AI
- DS specialists working on advanced models
Agenda
- Fundamentals of linear algebra in ML
- Vectors and vector spaces
- Matrices and matrix operations
- Linear transformations
- Systems of linear equations in ML
- Advanced algebraic concepts
- Eigenvalues and vectors
- Matrix distribution (SVD, PCA)
- Gradient optimization
- Standards and metrics in ML
- Applications in machine learning
- Algebra in linear regression
- Dimensionality reduction
- Kernel methods
- Neural networks and algebra
- Implementation and optimization
- Efficient matrix calculations
- Numerical libraries
- Performance optimization
- Solving numerical problems
Benefits
Upon completion of the training, the participant will have a deep understanding of the mathematical foundations of machine learning. He will gain the ability to effectively use algebraic concepts in the design and optimization of ML algorithms. Will develop the ability to analyze and solve mathematical problems that arise in machine learning projects. Will learn to implement advanced linear algebra techniques in the context of ML. Will be able to optimize matrix calculations in their solutions. Will gain the ability to interpret mathematical results in the context of practical ML applications.
Required preparation of participants
- Basic knowledge of higher mathematics
- Experience in Python programming
- Knowledge of the basics of machine learning
- Understanding of basic algebraic concepts
Issues
- Vector spaces in ML
- Array operations
- Linear transformations
- Eigenvalues and vectors
- Matrix distribution
- Gradient optimization
- Metrics of space
- Algebra in neural networks
- Numerical calculations
- Kernel methods
- Dimensionality reduction
- Numerical stability
Do you have any questions?
Feel free to contact us.
Patrycja Petkowska
+48 735 257 272
patrycja.petkowska@eitt.academy
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.
Patrycja Petkowska
+48 735 257 272
patrycja.petkowska@eitt.academy
31 Ząbkowska Street 03-736 Warsaw
FAQ - Frequently Asked Questions
- One-pager invitation with deadlines
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- Communication and Cooperation. Conflict management
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- Best practices workshop - retrospective; creating a coherent program for middle and lower management levels























