This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch.

Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

Explore the role of activation functions in deep learning and how they help neural networks learn complex patterns.

Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved ...

Deep learning is a subset of machine learning which uses neural networks to perform learning and predictions. Deep learning has shown amazing performance in various tasks, whether it be text, time ...

Deep learning systems—a type of unsupervised machine learning—are increasingly used with neural networks. They’re called “deep learning” because they contain large numbers of neural layers.

The deep learning pioneers believe that better neural network architectures will eventually lead to all aspects of human and animal intelligence, including symbol manipulation, reasoning, causal ...

He is also a co-founder of Coursera and has previously taught popular online courses on machine learning, neural networks and deep learning.

In the machine learning world, the sizes of artificial neural networks — and their outsize successes — are creating conceptual conundrums. When a network named AlexNet won an annual image recognition ...

Same as 5900-14 Specialization: Standalone course Instructor: Dr. Ioana Fleming, Instructor of Computer Science and Co-Associate Chair for Undergraduate Education Prior knowledge needed: Basic ...