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LeNet: Recognizing Handwritten Digits
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...
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Visualizing network architectures using Keras and TensorFlow
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...
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A gentle guide to training your first CNN with Keras and TensorFlow
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...
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Load a trained Keras/TensorFlow model from disk
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...
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MiniVGGNet: Going Deeper with CNNs
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...
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Save your Keras and TensorFlow model to disk
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...
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Grid search hyperparameter tuning with scikit-learn ( GridSearchCV )
In this tutorial, you will learn how to grid search hyperparameters using the scikit-learn machine learning library and the GridSearchCV class. We’ll apply the grid search to a computer vision...
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Hyperparameter tuning for Deep Learning with scikit-learn, Keras, and TensorFlow
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...
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Easy Hyperparameter Tuning with Keras Tuner and TensorFlow
In this tutorial, you will learn how to use the Keras Tuner package for easy hyperparameter tuning with Keras and TensorFlow. This tutorial is part four in our four-part series on hyperparameter...
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A gentle introduction to tf.data with TensorFlow
In this tutorial, you will learn the basics of TensorFlow’s tf.data module used to build faster, more efficient deep learning data pipelines. This blog post is part one in our three part series on...
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Data pipelines with tf.data and TensorFlow
In this tutorial, you will learn how to implement fast, efficient data pipelines for training neural networks using tf.data and TensorFlow. This tutorial is part two in our three part series on the...
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Data augmentation with tf.data and TensorFlow
In this tutorial, you will learn two methods to incorporate data augmentation into your tf.data pipeline using Keras and TensorFlow. This tutorial is part in our three part series on the tf.data...
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How to use the ModelCheckpoint callback with Keras and TensorFlow
Previously, we discussed how to save and serialize your models to disk after training is complete. We also learned how to spot underfitting and overfitting as they are happening, enabling you to kill...
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What is PyTorch?
In this tutorial, you will learn about the PyTorch deep learning library, including: What PyTorch isHow to install PyTorch on your machineImportant PyTorch features, including tensors and autogradHow...
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Intro to PyTorch: Training your first neural network using PyTorch
In this tutorial, you will learn how to train your first neural network using the PyTorch deep learning library. This tutorial is part two in our five part series on PyTorch deep learning...
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Smile detection with OpenCV, Keras, and TensorFlow
In this tutorial, we will be building a complete end-to-end application that can detect smiles in a video stream in real-time using deep learning along with traditional computer vision techniques. To...
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Breaking captchas with deep learning, Keras, and TensorFlow
In the past, we’ve worked with datasets that have been pre-compiled and labeled for us — but what if we wanted to go about creating our own custom dataset and then training a CNN on it? In this...
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PyTorch: Training your first Convolutional Neural Network (CNN)
In this tutorial, you will receive a gentle introduction to training your first Convolutional Neural Network (CNN) using the PyTorch deep learning library. This network will be able to recognize...
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An interview with Askat Kuzdeuov, computer vision and deep learning researcher
In this blog post, I interview Askat Kuzdeuov, a computer vision and deep learning researcher at the Institute of Smart Systems and Artificial Intelligence (ISSAI). Askat is not only a stellar...
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PyTorch image classification with pre-trained networks
In this tutorial, you will learn how to perform image classification with pre-trained networks using PyTorch. Utilizing these networks, you can accurately classify 1,000 common object categories in...
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