Deep learning

Traditional Neural Networks

• Traditional Neural Networks
• Perceptron
• Perceptron as a binary classifier
• Multiclass classification using a perceptron
• Classifying handwritten digits
• Binary classification using Keras
• Multilayer binary classifier
• Deep neural network on MNIST using Keras
• Multilayer binary classifier

Convolutional Neural Networks (CNNs)

• Convolutional Neural Networks (CNNs)
• Wine quality
• Churn
• Recognizing handwritten digits with CNN using Keras
• Classifying cats versus dogs with data generators
• CIFAR10 image classification

Natural Language Processing (NLP)

• Natural Language Processing (NLP)
• Classical approaches to text representation
• Distributed representation for text
• Text preprocessing of the ‘Alice in Wonderland’ text

Recurrent Neural Networks (RNNs)

• Recurrent Neural Networks (RNNs)
• Forward pass of a Simple RNN
• Apple stock price prediction
• IBM stock price prediction

LSTMs, GRUs, and Advanced RNNs

• LSTMs, GRUs, and Advanced RNNs
• Sentiment classification with RNN
• LSTM-Based sentiment classification model
• GRU-Based sentiment classification model
• Bidirectional LSTM-based sentiment classification model
• Stacked LSTM-based sentiment classification model

Generative Adversarial Networks (GANs)

• Generative Adversarial Networks (GANs)
• Generating a data distribution from a known function
• Building a generator network
• Building a discriminator network
• Building a GAN network

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