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A Brief Introduction to BERT

As we learned what a Transformer is and how we might train the Transformer model, we notice that it is a great tool to make a computer understand human language. However, the Transformer was originally designed as a model to translate one language to another. If we repurpose it for a different task, we would […]

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Data Engineering for ML: Optimize for Cost Efficiency

Sponsored Post     Over the past few years, a lot has changed in the world of stream processing systems. This is especially true as companies manage larger amounts of data than ever before.  In fact, roughly 2.5 quintiliion bytes worth of data are generated every day. Manually processing the sheer amount of data that […]

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Interactive Machine Learning Live Course with Dr. Kirk Borne

Sponsored Post     Apply now to join Dr. Kirk Borne’s live interactive course, starting on November 28.  Explore Machine Learning Live with hands-on labs and real world applications with Dr. Kirk Borne, ex-NASA Scientist and former Principal Data Scientist at Booz Allen Hamilton. He was also a professor of Astrophysics and Computational Science at […]

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Inferencing the Transformer Model

We have seen how to train the Transformer model on a dataset of English and German sentence pairs and how to plot the training and validation loss curves to diagnose the model’s learning performance and decide at which epoch to run inference on the trained model. We are now ready to run inference on the […]

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Attend the Data Science Symposium 2022

Sponsored Post      Attend the Data Science Symposium 2022 on November 8 The Center for Business Analytics at the University of Cincinnati will present its annual Data Science Symposium 2022 on November 8. This all day in-person event will have three featured speakers and two tech talk tracks with four concurrent presentations in each track. The […]

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Training the Transformer Model

We have put together the complete Transformer model, and now we are ready to train it for neural machine translation. We shall use a training dataset for this purpose, which contains short English and German sentence pairs. We will also revisit the role of masking in computing the accuracy and loss metrics during the training […]

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Implementing the Transformer Decoder from Scratch in TensorFlow and Keras

There are many similarities between the Transformer encoder and decoder, such as their implementation of multi-head attention, layer normalization, and a fully connected feed-forward network as their final sub-layer. Having implemented the Transformer encoder, we will now go ahead and apply our knowledge in implementing the Transformer decoder as a further step toward implementing the […]

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Implementing the Transformer Encoder from Scratch in TensorFlow and Keras

Having seen how to implement the scaled dot-product attention and integrate it within the multi-head attention of the Transformer model, let’s progress one step further toward implementing a complete Transformer model by applying its encoder. Our end goal remains to apply the complete model to Natural Language Processing (NLP). In this tutorial, you will discover how […]

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