You can master Computer Vision, Deep Learning, and OpenCV - PyImageSearch
I publish a brand new Computer Vision, Deep Learning, and OpenCV tutorial every Monday at 10AM EST. Here you'll find my most recent tutorials and guides.
In this tutorial, you will learn how to use the Keras Tuner package for easy hyperparameter tuning with Keras and TensorFlow. A sizable dataset is necessary when working with hyperparameter tuning. It allows us to understand the effects of different…
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In this tutorial, you will learn how to tune the hyperparameters of a deep neural network using scikit-learn, Keras, and TensorFlow. This tutorial is part three in our four-part series on hyperparameter tuning: Introduction to hyperparameter tuning with scikit-learn and…
Read More of Hyperparameter tuning for Deep Learning with scikit-learn, Keras, and TensorFlow
In this tutorial, you will learn how to use the GridSearchCV class to do grid search hyperparameter tuning using the scikit-learn machine learning library. We’ll apply the grid search to a computer vision project. This blog post is part two…
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One concept we have not discussed yet is architecture visualization, the process of constructing a graph of nodes and associated connections in a network and saving the graph to disk as an image (i.e., PNG, JPG, etc.). Nodes in the…
Read More of Visualizing network architectures using Keras and TensorFlow
In our previous tutorial, we discussed LeNet, a seminal Convolutional Neural Network in the deep learning and computer vision literature. VGGNet, (sometimes referred to as simply VGG), was first introduced by Simonyan and Zisserman in their 2014 paper, Very Deep…
Read More of MiniVGGNet: Going Deeper with CNNs
The LeNet architecture is a seminal work in the deep learning community, first introduced by LeCun et al. in their 1998 paper, Gradient-Based Learning Applied to Document Recognition. As the name of the paper suggests, the authors’ motivation behind implementing…
Read More of LeNet: Recognizing Handwritten Digits
Now that we’ve trained our model and serialized it, we need to load it from disk. As a practical application of model serialization, I’ll be demonstrating how to classify individual images from the Animals dataset and then display the classified…
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In our previous tutorial, you learned how to train your first Convolutional Neural Network using the Keras library. However, you might have noticed that each time you wanted to evaluate your network or test it on a set of images,…
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In this tutorial, you will implement a CNN using Python and Keras. We’ll start with a quick review of Keras configurations you should keep in mind when constructing and training your own CNNs. We’ll then implement ShallowNet, which as the…
Read More of A gentle guide to training your first CNN with Keras and TensorFlow
