Deep Learning Applications | Neural Networks | AI Course

Explore the latest advancements in deep learning and its practical applications in computer vision, time series, security, NLP, and data generation.

Introduction

Deep learning is a group of exciting new technologies for neural networks. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered.

Highlights

• Covers a wide range of deep learning architectures and their applications
• Hands-on experience using Python, TensorFlow, and Keras
• Focuses on practical application of deep learning to real-world problems
• Includes High Performance Computing (HPC) aspects for leveraging GPUs and grids

Recommendation

This course is recommended for students and professionals interested in exploring the latest advancements in deep learning and its practical applications. No prior knowledge of Python is required, but familiarity with at least one programming language is assumed.