You can master Computer Vision, Deep Learning, and OpenCV - PyImageSearch
The first time I ever used the Tesseract optical character recognition (OCR) engine was in my college undergraduate years. A dataset comprising diverse textual images is necessary for an OCR project. It enables the OCR system to learn different text…
Read More of Your First OCR Project with Tesseract and Python
In this tutorial, we will configure our development environment for OCR. Once your machine is configured, we’ll start writing Python code to perform OCR, paving the way for you to develop your own OCR applications. A text-image dataset is useful…
Read More of Installing Tesseract, PyTesseract, and Python OCR packages on your system
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 handwritten Hiragana characters. In training a Convolutional Neural Network (CNN),…
Read More of PyTorch: Training your first Convolutional Neural Network (CNN)
In this tutorial, you will learn about the PyTorch deep learning library, including: What PyTorch is How to install PyTorch on your machine Important PyTorch features, including tensors and autograd How PyTorch supports GPUs Why PyTorch is so popular among…
Read More of What is PyTorch?
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…
Read More of How to use the ModelCheckpoint callback with Keras and TensorFlow
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…
Read More of Data augmentation with tf.data and 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. A good dataset is necessary when working with tf.data in TensorFlow. It allows us to understand how to…
Read More of A gentle introduction to tf.data with TensorFlow
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…
Read More of Easy Hyperparameter Tuning with Keras Tuner and TensorFlow
CNN Building Blocks Neural networks accept an input image/feature vector (one input node for each entry) and transform it through a series of hidden layers, commonly using nonlinear activation functions. Each hidden layer is also made up of a set…
Read More of Convolutional Neural Networks (CNNs) and Layer Types
