Search results for "word embedding"

Sequence Classification with LSTM Recurrent Neural Networks in Python with Keras

Sequence Classification with LSTM Recurrent Neural Networks in Python with Keras

Sequence classification is a predictive modeling problem where you have some sequence of inputs over space or time and the task is to predict a category for the sequence. What makes this problem difficult is that the sequences can vary in length, be comprised of a very large vocabulary of input symbols and may require […]

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Predict Sentiment From Movie Reviews Using Deep Learning

How to Predict Sentiment From Movie Reviews Using Deep Learning (Text Classification)

Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted. In this post, you will discover how you can predict the sentiment of movie reviews as either positive or negative in Python using the Keras deep learning library. After reading this post you will know: About the […]

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Machine Learning Mastery

Start Here with Machine Learning

Need Help Getting Started with Applied Machine Learning? These are the Step-by-Step Guides that You’ve Been Looking For! What do you want help with? The most common question I’m asked is: “how do I get started?” My best advice for getting started in machine learning is broken down into a 5-step process: Step 1: Adjust Mindset. […]

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Example of 100 Photos of Sneakers Generated by an AC-GAN

How to Develop an Auxiliary Classifier GAN (AC-GAN) From Scratch with Keras

Generative Adversarial Networks, or GANs, are an architecture for training generative models, such as deep convolutional neural networks for generating images. The conditional generative adversarial network, or cGAN for short, is a type of GAN that involves the conditional generation of images by a generator model. Image generation can be conditional on a class label, […]

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Line Plot for Supervised Greedy Layer-Wise Pretraining Showing Model Layers vs Train and Test Set Classification Accuracy on the Blobs Classification Problem

How to Use Greedy Layer-Wise Pretraining in Deep Learning Neural Networks

Training deep neural networks was traditionally challenging as the vanishing gradient meant that weights in layers close to the input layer were not updated in response to errors calculated on the training dataset. An innovation and important milestone in the field of deep learning was greedy layer-wise pretraining that allowed very deep neural networks to […]

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Overview of Course Structure

Practical Deep Learning for Coders (Review)

Practical deep learning is a challenging subject in which to get started. It is often taught in a bottom-up manner, requiring that you first get familiar with linear algebra, calculus, and mathematical optimization before eventually learning the neural network techniques. This can take years, and most of the background theory will not help you to […]

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Promise of Deep Learning for Natural Language Processing

Promise of Deep Learning for Natural Language Processing

The promise of deep learning in the field of natural language processing is the better performance by models that may require more data but less linguistic expertise to train and operate. There is a lot of hype and large claims around deep learning methods, but beyond the hype, deep learning methods are achieving state-of-the-art results on […]

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