About This Course
Deep learning is a subfield of machine learning that’s inspired much of the recent innovation in artificial intelligence (AI). Built on neural networks, deep learning is influenced by how the human brain works. Deep learning has led to advances in everything from image, audio and video classification to content generation, which has the potential to replicate human creativity. In this course, you’ll gain both a theoretical understanding of deep learning and hands-on experience with emerging use cases.
What You'll Learn
The underlying conceptual principles of neural networks
Deep learning techniques such as dropout and batch normalization
How to select appropriate loss functions, optimizers and activation functions
The application of CNNs, RNNs, transformers and more
How to build computer vision models, large language models (LLMs) and game-playing agents
Get Hands-On Experience
Gain hands-on experience with cutting-edge methods in deep learning
Build models using popular open-source tools such as Keras and TensorFlow
Leverage LLMs to create a wrapper and accelerate development
