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Tag: deep learning

Using ReLU, Sigmoid and Tanh with PyTorch, Ignite and Lightning

Using ReLU, Sigmoid and Tanh with PyTorch, Ignite and Lightning

Chris21 January 202121 January 2021Leave a comment
Rectified Linear Unit, Sigmoid and Tanh are three activation functions that play an important role in how neural networks work....
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Binary Crossentropy Loss with PyTorch, Ignite and Lightning

Binary Crossentropy Loss with PyTorch, Ignite and Lightning

Chris20 January 202120 January 2021Leave a comment
Training a deep learning model is a cyclical process. First, you feed forward data, generating predictions for each sample. Then,...
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Object Detection for Images and Videos with TensorFlow 2.0

Object Detection for Images and Videos with TensorFlow 2.0

Chris15 January 202118 January 2021Leave a comment
Object detection is one of the areas in Deep Learning where much progress has been made. Using a variety of...
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Getting started with PyTorch

Getting started with PyTorch

Chris13 January 202120 January 2021Leave a comment
When you want to build a deep learning model these days, there are two machine learning libraries that you must...
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Using SELU with TensorFlow 2.0 and Keras

Using SELU with TensorFlow 2.0 and Keras

Chris12 January 202120 January 2021Leave a comment
Neural networks thrive on nonlinear data only when nonlinear activation functions are used. The Rectified Linear Unit, or RELU, is...
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Bidirectional LSTMs with TensorFlow 2.0 and Keras

Bidirectional LSTMs with TensorFlow 2.0 and Keras

Chris11 January 202120 January 2021Leave a comment
Long Short-Term Memory networks or LSTMs are Neural Networks that are used in a variety of tasks. Used in Natural...
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Build an LSTM Model with TensorFlow 2.0 and Keras

Build an LSTM Model with TensorFlow 2.0 and Keras

Chris7 January 202120 January 20211 Comment
Long Short-Term Memory (LSTM) based neural networks have played an important role in the field of Natural Language Processing. In...
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ALBERT explained: A Lite BERT

ALBERT explained: A Lite BERT

Chris6 January 20216 January 2021Leave a comment
Transformer models like GPT-3 and BERT have been really prominent in today’s Natural Language Processing landscape. They have built upon...
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Differences between Autoregressive, Autoencoding and Sequence-to-Sequence Models in Machine Learning

Differences between Autoregressive, Autoencoding and Sequence-to-Sequence Models in Machine Learning

Chris29 December 20202 January 20214 Comments
Transformers have changed the application of Machine Learning in Natural Language Processing. They have replaced LSTMs as state-of-the-art (SOTA) approaches...
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A gentle introduction to Long Short-Term Memory Networks (LSTM)

A gentle introduction to Long Short-Term Memory Networks (LSTM)

Chris29 December 202013 January 20217 Comments
One of the fields where Machine Learning has boosted progress is Natural Language Processing. This is particularly true for the...
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