A Standard Multivariate, Multi-Step, and Multi-Site Time Series Forecasting Problem

A Standard Multivariate, Multi-Step, and Multi-Site Time Series Forecasting Problem

Real-world time series forecasting is challenging for a whole host of reasons not limited to problem features such as having multiple input variables, the requirement to predict multiple time steps, and the need to perform the same type of prediction for multiple physical sites. In this post, you will discover a standardized yet complex time […]

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How to Install XGBoost for Python on macOS

How to Install XGBoost for Python on macOS

XGBoost is a library for developing very fast and accurate gradient boosting models. It is a library at the center of many winning solutions in Kaggle data science competitions. In this tutorial, you will discover how to install the XGBoost library for Python on macOS. Let’s get started. Tutorial Overview This tutorial is divided into […]

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Scatter plot of Moons Test Classification Problem

How to Generate Test Datasets in Python with scikit-learn

Test datasets are small contrived datasets that let you test a machine learning algorithm or test harness. The data from test datasets have well-defined properties, such as linearly or non-linearity, that allow you to explore specific algorithm behavior. The scikit-learn Python library provides a suite of functions for generating samples from configurable test problems for […]

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Plot of the Multichannel Convolutional Neural Network For Text

How to Develop an N-gram Multichannel Convolutional Neural Network for Sentiment Analysis

A standard deep learning model for text classification and sentiment analysis uses a word embedding layer and one-dimensional convolutional neural network. The model can be expanded by using multiple parallel convolutional neural networks that read the source document using different kernel sizes. This, in effect, creates a multichannel convolutional neural network for text that reads […]

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How to Develop a Neural Machine Translation System in Keras

How to Develop a Neural Machine Translation System in Keras from Scratch

Machine translation is a challenging task that traditionally involves large statistical models developed using highly sophisticated linguistic knowledge. Neural machine translation is the use of deep neural networks for the problem of machine translation. In this tutorial, you will discover how to develop a neural machine translation system for translating German phrases to English. After […]

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How to Prepare a French-to-English Dataset for Machine Translation

How to Prepare a French-to-English Dataset for Machine Translation

Machine translation is the challenging task of converting text from a source language into coherent and matching text in a target language. Neural machine translation systems such as encoder-decoder recurrent neural networks are achieving state-of-the-art results for machine translation with a single end-to-end system trained directly on source and target language. Standard datasets are required […]

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How to Implement Beam Search Decoder for Natural Language Processing

How to Implement a Beam Search Decoder for Natural Language Processing

Natural language processing tasks, such as caption generation and machine translation, involve generating sequences of words. Models developed for these problems often operate by generating probability distributions across the vocabulary of output words and it is up to decoding algorithms to sample the probability distributions to generate the most likely sequences of words. In this […]

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How to Configure an Encoder-Decoder Model for Neural Machine Translation

How to Configure an Encoder-Decoder Model for Neural Machine Translation

The encoder-decoder architecture for recurrent neural networks is achieving state-of-the-art results on standard machine translation benchmarks and is being used in the heart of industrial translation services. The model is simple, but given the large amount of data required to train it, tuning the myriad of design decisions in the model in order get top […]

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Encoder-Decoder Recurrent Neural Network Models for Neural Machine Translation

Encoder-Decoder Recurrent Neural Network Models for Neural Machine Translation

The encoder-decoder architecture for recurrent neural networks is the standard neural machine translation method that rivals and in some cases outperforms classical statistical machine translation methods. This architecture is very new, having only been pioneered in 2014, although, has been adopted as the core technology inside Google’s translate service. In this post, you will discover […]

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