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...
TensorFlow Eager Execution: what is it?
Looking at the Effective TensorFlow 2 guide, we can see what major changes have occurred between TensorFlow 1 and 2.x....
Automating neural network configuration with Keras Tuner
Machine learning has been around for many decades now. Starting with the Rosenblatt Perceptron in the 1950s, followed by Multilayer...
Best Machine Learning & Artificial Intelligence Books Available in 2020
Quite recently, one of my colleagues asked me to give some tips for books about machine learning. In his case,...
How to visualize support vectors of your SVM classifier?
In today’s world filled with buzz about deep neural networks, Support Vector Machines remain a widely used class of machine...
How to create a confusion matrix with Scikit-learn?
After training a supervised machine learning model such as a classifier, you would like to know how well it works....
Creating a simple binary SVM classifier with Python and Scikit-learn
Suppose that you are cleaning your house – and especially the clothes you never wear anymore. For every item, you...
Visualizing gradient importance with Vanilla Gradients and tf-explain
Machine learning and deep learning are here to stay. After the spectacular rise of deep learning since 2012, much research...
Neural network Activation Visualization with tf-explain
Deep learning models and especially neural networks have been used thoroughly over the past few years. There are many success...
