Technologies / Artificial Intelligence

OpenNMT: Configuring a machine translation system

The training introduces participants to the world of neural machine translation through hands-on work with the OpenNMT platform. During the workshop, participants will learn the process of building, training and implementing NMT models from scratch. The program focuses on the practical aspects of configuring and optimizing translation systems, taking into account the specifics of different language pairs and application domains.The training provides a solid theoretical and practical foundation in deep learning. During an intensive workshop, participants learn the foundations of neural networks, techniques for training them and practical applications in various domains. The program combines mathematical theory with practical implementation of models, placing special emphasis on understanding the mechanisms of deep neural networks and their effective use in real projects.

Issues

OpenNMT architecture
Preprocessing of language data
Text Tokenization
Transformer architectures
NMT model training
Translation evaluation
Fine-tuning of models
Serving API
Quality monitoring
System upgrade
Error analysis
Best practices NMT
----------|------------- Subcategory | Artificial Intelligence Training code | IT-AI-160 Duration | 3 days (24 hours) Price net/person | 3750 PLN.
Neural network architecture
Activation functions
Back propagation
Gradient optimization
Regularization and dropout
Convolutional networks
Recursive networks
Transformers
Data preparation
Training strategies
Validation of models
Implementing solutions

Benefits

Practical knowledge in the configuration and implementation of neural machine translation systems
To prepare and process linguistic data for training NMT models
Will learn methods for optimizing translation quality for different language pairs
Will be able to implement and manage translation systems in a production environment
Will develop the ability to evaluate and improve the quality of machine translation
Will gain knowledge of NMT best practices.The participant will gain a thorough understanding of the theoretical foundations of deep learning and practical model implementation skills
To independently design and train different types of neural networks tailored to specific tasks
Methods for efficient optimization and regularization of deep learning models
Will be able to diagnose and solve typical problems that occur during training of deep networks
Will gain the ability to select the appropriate network architecture for the specific task
Will develop practical skills in implementing models in popular frameworks

Who is this training for?

NLP specialists working on translation systems

ML engineers interested in language processing

Computer linguists

Language system developers

Researchers in the field of NLP

Software localization specialists

Programmers getting started with deep learning

Data Scientists expanding their skills

ML engineers interested in neural networks

Data analysts entering the field of deep learning

Scientists and researchers from various fields

Specialists in computer vision and natural language processing

Prerequisites

Basic knowledge of machine learning
Knowledge of NLP issues
Experience working with Python
General linguistic knowledge
Knowledge of the basics of machine learning
A solid mathematical foundation (linear algebra, differential calculus)
Ability to program in Python
Basic knowledge of statistics

Training program

Preparation of the environment
Language data management

Configuration of models
Transformer architectures
Tokenization and dictionaries

Validation of models
Training and evaluation

Quality assessment metrics
Fine-tuning of models
Error analysis
Implementation of the system
Serving models
API integration

Update models
Foundations of deep learning
Neural network architecture
Activation functions and back propagation
Optimization and regularization
Initialization of weights and normalization
Neural network architectures
Convolutional Networks (CNN)
Recurrent networks (RNNs)
Transformers
Generative networks
Training models
Data preparation
Training strategies
Validation and evaluation

Implementation and optimization
Framework'i deep learning
Performance optimization
Implementing models

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

Who is the OpenNMT: Configuring a machine translation system training for?

This training is designed for professionals looking to develop skills in opennmt: configuring a machine translation system. Required level: intermediate.

How long is the OpenNMT: Configuring a machine translation system training?

The training lasts 1. Available in online or on-site format.

Will I receive a certificate?

Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.

Can this training be conducted for a closed group?

Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.