### The vanishing gradient problem and ReLUs – a TensorFlow investigation

Deep learning is huge in machine learning at the moment, and no wonder – it is making large and important strides in solving problems in computer […]

Deep learning is huge in machine learning at the moment, and no wonder – it is making large and important strides in solving problems in computer […]

Consuming data efficiently becomes really paramount to training performance in deep learning. In a previous post I discussed the TensorFlow data queuing framework. However, TensorFlow […]

In this post, I’m going to introduce the concept of reinforcement learning, and show you how to build an autonomous agent that can successfully play […]

In previous posts, I introduced Keras for building convolutional neural networks and performing word embedding. The next natural step is to talk about implementing recurrent […]

In my previous tutorial on recurrent neural networks and LSTM networks in TensorFlow, we weren’t able to get fantastic results. This is because I was […]

So – if you’re a follower of this blog and you’ve been trying out your own deep learning networks in TensorFlow and Keras, you’ve probably […]

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 […]

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