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Technologies / Artificial Intelligence

OpenNN: Implementation of neural networks

The training focuses on practical implementation of neural networks using the OpenNN library. The program covers designing, training and optimizing neural models in a C++ environment. The workshop combines theoretical fundamentals with intensive programming, allowing participants to gain practical skills in creating efficient deep learning solutions.

Issues

  • OpenNN architecture

  • Implementation of neural layers

  • Activation functions

  • Training algorithms

  • Regularization of models

  • Performance optimization

  • Code profiling

  • System integration

  • Model testing

  • Performance monitoring

  • Debugging

  • Best practices

Benefits

  • The participant will gain practical skills in implementing neural networks in C++ using the OpenNN library
  • Will learn to design and optimize neural network architectures for specific applications
  • Will learn techniques for efficient training of models under hardware constraints
  • Will be able to integrate neural models into existing production systems
  • Will develop the ability to debug and profile the performance of deep learning implementations
  • Will gain knowledge of best practices in developing efficient AI solutions

Who is this training for?

C++ programmers interested in implementing neural networks
ML engineers looking for efficient solutions
Embedded systems developers
ML performance optimization specialists
Real-time application developers
Industrial systems engineers

Prerequisites

  • Advanced knowledge of C++
  • Basics of neural networks
  • Knowledge of linear algebra
  • Experience in code optimization

Training program

01

Library architecture

  • Configuring the environment
02

Basic components

  • Data management
  • Implementation of models
  • Network architecture design
03

Defining layers

  • Activation functions
  • Parameter initialization
  • Training and optimization
  • Training algorithms
04

Loss functions

  • Regularization
  • Optimization strategies
  • Production implementation
  • Integration with applications
  • Performance optimization
05

Model testing

  • Production monitoring

Delivery Methods

Online

  • Convenience of participating from anywhere
  • Interactive live sessions with trainer
  • Materials available for 30 days
  • No travel costs

On-site

  • Direct contact with trainer and group
  • Intensive hands-on workshops
  • Networking with other participants
  • Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For OpenNN: Implementation of neural networks we recommend: Advanced knowledge of C++; Basics of neural networks; Knowledge of linear algebra.

What is the format and duration of this training?

The training lasts 2 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: C++ programmers interested in implementing neural networks; ML engineers looking for efficient solutions; Embedded systems developers.

Monika Fengler
Monika Fengler Opiekun szkolenia

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Up to 100%

National Training Fund

Up to 100% funding for employers

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