### Recurrent neural networks and LSTM tutorial in Python and TensorFlow

In the deep learning journey so far on this website, I’ve introduced dense neural networks and convolutional neural networks (CNNs) which explain how to perform classification […]

In the deep learning journey so far on this website, I’ve introduced dense neural networks and convolutional neural networks (CNNs) which explain how to perform classification […]

I’ve been dedicating quite a bit of time recently to Word2Vec tutorials because of the importance of the Word2Vec concept for natural language processing (NLP) […]

Understanding Word2Vec word embedding is a critical component in your machine learning journey. Word embedding is a necessary step in performing efficient natural language processing […]

One of the great things about TensorFlow is its ability to handle multiple threads and therefore allow asynchronous operations. If we have large datasets this can […]

In previous tutorials (Python TensorFlow tutorial, CNN tutorial, and the Word2Vec tutorial) on deep learning, I have taught how to build networks in the TensorFlow deep […]

In coming tutorials on this blog I will be dealing with how to create deep learning models that predict text sequences. However, before we get […]

In a previous tutorial, I demonstrated how to create a convolutional neural network (CNN) using TensorFlow to classify the MNIST handwritten digit dataset. TensorFlow is a brilliant tool, […]

In the two previous tutorial posts, an introduction to neural networks and an introduction to TensorFlow, three layer neural networks were created and used to […]

Google’s TensorFlow has been a hot topic in deep learning recently. The open source software, designed to allow efficient computation of data flow graphs, is especially suited to […]

In the neural network tutorial, I introduced the gradient descent algorithm which is used to train the weights in an artificial neural network. In reality, […]

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