Tag Archives | virtual environments

macOS for deep learning with Python, TensorFlow, and Keras

In today’s tutorial, I’ll demonstrate how you can configure your macOS system for deep learning using Python, TensorFlow, and Keras. This tutorial is the final part of a series on configuring your development environment for deep learning. I created these tutorials to accompany my new book, Deep Learning for Computer Vision with Python; however, you […]

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Configuring Ubuntu for deep learning with Python

When it comes to learning new technology such as deep learning, configuring your development environment tends to be half the battle. Different operating systems, hardware, dependencies, and the actual libraries themselves can lead to many headaches before you’re even able to get started studying deep learning. These issues are further compounded by the speed of […]

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Pre-configured Amazon AWS deep learning AMI with Python

The Ubuntu VirtualBox virtual machine that comes with my book, Deep Learning for Computer Vision with Python, includes all the necessary deep learning and computer vision libraries you need (such as Keras, TensorFlow, scikit-learn, scikit-image, OpenCV, etc.) pre-installed. However, while the deep learning virtual machine is easy to use, it also has a number of drawbacks, […]

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Creating a face detection API with Python and OpenCV (in just 5 minutes)

So you’ve just built your first awesome computer vision app. Maybe it can detect faces in images. Or maybe your app can recognize prescription pills in photos. Or maybe your computer vision app can identify the covers of top selling books, all while displaying the latest reader reviews and the cheapest websites online to purchase them. So the big […]

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