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Getting started with the NVIDIA Jetson Nano
In this tutorial, you will learn how to get started with your NVIDIA Jetson Nano, including: First boot Installing system packages and prerequisites Configuring your Python development environment...
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Object detection and image classification with Google Coral USB Accelerator
A few weeks ago I published a tutorial on how to get started with the Google Coral USB Accelerator. That tutorial was meant to help you configure your device and run your first demo script. Today we...
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Transfer Learning with Keras and Deep Learning
In this tutorial, you will learn how to perform transfer learning with Keras, Deep Learning, and Python on your own custom datasets. Imagine this: You’re just hired by Yelp to work in their computer...
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Keras: Feature extraction on large datasets with Deep Learning
In this tutorial, you will learn how to use Keras for feature extraction on image datasets too big to fit into memory. You’ll utilize ResNet-50 (pre-trained on ImageNet) to extract features from a...
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Fine-tuning with Keras and Deep Learning
In this tutorial, you will learn how to perform fine-tuning with Keras and Deep Learning. We will take a CNN pre-trained on the ImageNet dataset and fine-tune it to perform image classification and...
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Keras Mask R-CNN
In this tutorial, you will learn how to use Keras and Mask R-CNN to perform instance segmentation (both with and without a GPU). Using Mask R-CNN we can perform both: Object detection, giving us the...
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Online/Incremental Learning with Keras and Creme
In this tutorial, you will learn how to perform online/incremental learning with Keras and Creme on datasets too large to fit into memory. A few weeks ago I showed you how to use Keras for feature...
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Change input shape dimensions for fine-tuning with Keras
In this tutorial, you will learn how to change the input shape tensor dimensions for fine-tuning using Keras. After going through this guide you’ll understand how to apply transfer learning to images...
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Keras ImageDataGenerator and Data Augmentation
In today’s tutorial, you will learn how to use Keras’ ImageDataGenerator class to perform data augmentation. I’ll also dispel common confusions surrounding what data augmentation is, why we use data...
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Keras learning rate schedules and decay
In this tutorial, you will learn about learning rate schedules and decay using Keras. You’ll learn how to use Keras’ standard learning rate decay along with step-based, linear, and polynomial learning...
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Cyclical Learning Rates with Keras and Deep Learning
In this tutorial, you will learn how to use Cyclical Learning Rates (CLR) and Keras to train your own neural networks. Using Cyclical Learning Rates you can dramatically reduce the number of...
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Keras Learning Rate Finder
In this tutorial, you will learn how to automatically find learning rates using Keras. This guide provides a Keras implementation of fast.ai’s popular “lr_find” method. Today is part three in our...
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An interview with Kapil Varshney, Data Scientist at Esri R&D
In today’s blog post, I interview Kapil Varshney, a PyImageSearch reader who was recently hired at Esri Research and Development as a Data Scientist focusing on Computer Vision and Deep Learning....
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Keras: Starting, stopping, and resuming training
In this tutorial, you will learn how to use Keras to train a neural network, stop training, update your learning rate, and then resume training from where you left off using the new learning rate....
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Rectified Adam (RAdam) optimizer with Keras
In this tutorial, you will learn how to use Keras and the Rectified Adam optimizer as a drop-in replacement for the standard Adam optimizer, potentially leading to a higher accuracy model (and in...
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Is Rectified Adam actually *better* than Adam?
Is the Rectified Adam (RAdam) optimizer actually better than the standard Adam optimizer? According to my 24 experiments, the answer is no, typically not (but there are cases where you do want to use...
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Why is my validation loss lower than my training loss?
In this tutorial, you will learn the three primary reasons your validation loss may be lower than your training loss when training your own custom deep neural networks. I first became interested in...
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Keras vs. tf.keras: What’s the difference in TensorFlow 2.0?
In this tutorial you’ll discover the difference between Keras and tf.keras , including what’s new in TensorFlow 2.0. Today’s tutorial is inspired from an email I received last Tuesday from...
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3 ways to create a Keras model with TensorFlow 2.0 (Sequential, Functional,...
Keras and TensorFlow 2.0 provide you with three methods to implement your own neural network architectures: Sequential API Functional API Model subclassing Inside of this tutorial you’ll learn how to...
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Traffic Sign Classification with Keras and Deep Learning
In this tutorial, you will learn how to train your own traffic sign classifier/recognizer capable of obtaining over 95% accuracy using Keras and Deep Learning. Last weekend I drove down to Maryland to...
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