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Long Short-Term Memory (LSTM) LSTM (Long Short-Term Memory) networks are one of the most important inventions in deep learning. They are a special type of Recurrent Neural Network (RNN) designed.

Recurrent Neural Networks (RNNs) While Convolutional Neural Networks (CNNs) are designed to process images, Recurrent Neural Networks (RNNs) are designed for sequence-based data — data that changes with time or.

Convolutional Neural Networks (CNNs) CNNs are one of the most powerful deep learning architectures ever created. They are the reason behind breakthroughs in computer vision — including face recognition, self-driving.

Introduction to TensorFlow and Keras After understanding neural networks, perceptrons, activation functions, and backpropagation, it’s time to explore how deep learning is built in the real world. The most popular.

Forward and Backpropagation In the earlier chapters, you learned about perceptrons, neural networks, and activation functions. Now it’s time to understand the heart of every deep learning model: Forward Propagation.

Activation Functions Activation functions are one of the most important concepts in deep learning. Without activation functions, a neural network becomes nothing more than a simple linear equation—unable to learn.

Perceptron and Multilayer Perceptron (MLP) In the previous chapters, you learned about deep learning and the basics of neural networks. Now it’s time to study the most fundamental building block.

Neural Networks Basics Neural Networks are the foundation of Deep Learning. They are inspired by the structure and functioning of the human brain. Just like our brain has billions of.

Introduction to Deep Learning Deep Learning is one of the most powerful fields in modern computer science. It gives computers the ability to learn from experience, understand patterns, and make.