Search Results for: argparse python

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 accomplish this task, we’ll be training the LetNet architecture…

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 off experiments that are not performing well…

In this tutorial, you will learn two methods to incorporate data augmentation into your tf.data pipeline using Keras and TensorFlow. A good dataset of images is vital when working with data augmentation in TensorFlow. It enables us to see how…

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 tf.data module: A gentle introduction to tf.data…

In this tutorial, you will learn the basics of TensorFlow’s tf.data module used to build faster, more efficient deep learning data pipelines. A good dataset is necessary when working with tf.data in TensorFlow. It allows us to understand how to…

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…

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…

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…

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,…