TensorFlow model optimization: an introduction to Pruning

Enjoying the benefits of machine learning models means that they are deployed in the field after training has finished. However,...

TensorFlow model optimization: an introduction to Quantization

Since the 2012 breakthrough in machine learning, spawning the hype around deep learning – that should have mostly passed by...

Looking at the Effective TensorFlow 2 guide, we can see what major changes have occurred between TensorFlow 1 and 2.x....

In machine learning, when performing supervised learning, you’ll have to load your dataset from somewhere – and then feed it...

So far, at MachineCurve, we have primarily focused on how to train models with Keras. This is nice, but a...

Convolutional neural networks are great tools for building image classifiers. They have been used thoroughly since the 2012 deep learning...

Visualizing your Keras model, whether it’s the architecture, the training process, the layers or its internals, is becoming increasingly important...

It’s very likely that you will use the ReLU activation function when creating a neural network. This is unsurprising, since...

If you want to visualize how your Keras model performs, it’s possible to use MachineCurve’s tutorial for visualizing the training...