Technologies / Artificial Intelligence

Advanced deep learning techniques

The training deepens the knowledge of advanced deep learning techniques, focusing on the latest developments in the field. During the workshop, participants will learn advanced neural network architectures, training and optimization methods, and learning transfer techniques. The program includes practical implementations of complex models and their application to challenging business scenarios.

Issues

Mechanisms of attention
Transformer architectures
Meta-learning
Federation learning
Distillation of knowledge
Distributed training
Quantization of models
Pruning the network
MLOps
Continuous training
Performance optimization
Monitoring of models

Benefits

The participant will master advanced techniques for designing and training complex deep learning models
Will gain the ability to implement and tune state-of-the-art neural network architectures
Will learn to effectively optimize the performance and scalability of deep learning models
Will be able to implement advanced ML solutions in a production environment
Will learn methods to effectively manage the lifecycle of deep learning models
Will develop the ability to adapt the latest developments in the field to practical applications

Who is this training for?

Experienced ML engineers working with deep learning

Data Scientists specializing in neural networks

Researchers developing new network architectures

Deep learning model optimization specialists

AI solution architects

Machine learning experts

Prerequisites

Practical experience in the implementation of neural networks
Advanced knowledge of mathematics and statistics
Proficiency in Python programming
Knowledge of deep learning frameworks

Training program

Hybrid architectures

Meta-learning
Optimization techniques
Advanced methods of regularization
Hyperparameter optimization techniques

Distillation of knowledge
Scalability and performance
Distributed training
Quantization of models

Inference optimization
Deployment to production
MLOps for deep learning
Monitoring and debugging

Model management

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 Advanced deep learning techniques we recommend: Practical experience in the implementation of neural networks; Advanced knowledge of mathematics and statistics; Proficiency in Python programming.

What is the format and duration of this training?

The training lasts 4 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: Experienced ML engineers working with deep learning; Data Scientists specializing in neural networks; Researchers developing new network architectures.