Deep Learning

Practical Projects Using CNN and RNN In this chapter, you will apply everything you have learned throughout the course. We.

Transfer Learning One of the biggest challenges in deep learning is the amount of data required. Training powerful models from.

Autoencoders Autoencoders are one of the most fascinating and useful deep learning architectures. They are designed to learn efficient representations.

Long Short-Term Memory (LSTM) LSTM (Long Short-Term Memory) networks are one of the most important inventions in deep learning. They.

Recurrent Neural Networks (RNNs) While Convolutional Neural Networks (CNNs) are designed to process images, Recurrent Neural Networks (RNNs) are designed.

Introduction to TensorFlow and Keras After understanding neural networks, perceptrons, activation functions, and backpropagation, it’s time to explore how deep.

Neural Networks Basics Neural Networks are the foundation of Deep Learning. They are inspired by the structure and functioning of.

Introduction to Deep Learning Deep Learning is one of the most powerful fields in modern computer science. It gives computers.