Hands-on workshop covering the latest developments in deep learning and neural networks
Join us for an intensive hands-on workshop on machine learning and deep learning. This workshop is designed for researchers, students, and professionals who want to gain practical experience with state-of-the-art machine learning techniques.
Participants will work with real datasets, implement neural networks from scratch, and explore advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer architectures.
Understand the mathematical foundations and architecture of neural networks
Build and train various neural network architectures from scratch
Learn best practices for training and optimizing machine learning models
Hands-on experience with TensorFlow and PyTorch frameworks
Explore practical applications and industry case studies
Learn to evaluate and interpret model performance metrics
Basic knowledge of Python syntax and data structures
Fundamental concepts in linear algebra and calculus
No prior experience required - we'll start from the basics
Check-in, setup, and introduction to the workshop
Fundamental concepts and mathematical foundations
Networking and refreshments
Practical implementation using Python and TensorFlow
Lunch provided, networking opportunity
Convolutional and recurrent neural networks
Refreshments and discussion
Practical applications and industry examples
Open discussion and networking session