Dive into the cutting-edge world of Deep Learning. This specialization provides a comprehensive understanding of neural networks, their architecture, and how to apply them to solve complex problems in areas like computer vision, natural language processing, and more.
Introduction to Neural Networks
Grasp the fundamental concepts of neural networks, including activation functions, backpropagation, and optimization algorithms. Build your first neural network from scratch.
Convolutional Neural Networks (CNNs)
Explore CNNs, the backbone of modern computer vision. Understand convolutional layers, pooling, and their application in image recognition and object detection.
Recurrent Neural Networks (RNNs) & LSTMs
Master RNNs and their advanced variants like LSTMs and GRUs for sequential data processing. Tackle tasks in time series analysis and natural language understanding.
Transformers & Advanced NLP
Delve into the revolutionary Transformer architecture, the driving force behind state-of-the-art NLP models like BERT and GPT. Understand attention mechanisms and their applications.
Deploying Deep Learning Models
Learn the essential skills for deploying your trained deep learning models into production environments using popular frameworks and tools.