Deep Learning Showcase
Keras Use Cases
Various Python scripts using Keras artificial neural networks to solve deep learning problems, such as Image Classification and LSTM Text Generation.
Neural Networks
Binary Classification with Keras
Implements a movie review classifier using the IMDB dataset that comes packaged with Keras.
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Multi-class Classification with Keras
Implements a news classifier using the Reuters dataset that comes packaged with Keras.
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Regression with Keras
Implements a housing price regression model using the Boston Housing Price dataset that comes packaged with Keras.
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Image Classification
Convnet with Keras - Digit Images
Implements a ConvNet model that classifies images in the MNIST digit dataset that comes packaged with Keras.
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Convnet with Keras - Color Images
Implements a ConvNet model that classifies images in the CIFAR10 small images dataset that comes packaged with Keras. This is a dataset of 50,000 32x32 color training images and 10,000 test images, labeled over 10 categories.
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Resnet with Keras
Performs images classification using Keras’ ResNet50 model.
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Recurrent Neural Networks
Text Processing
Transforms text input into tokens and convert those tokens into numeric vectors using one-hot encoding and feature hashing. Builds basic text-processing models using recurrent neural networks (RNN). Demonstrates how word embeddings such as Word2Vec can help improve the performance of text-processing models.
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References:
These files contain code from Deep Learning with Python, www.manning.com/books/deep-learning-with-python, Copyright 2018 Francois Chollet