The Telecom Business Hall APP, as the entry-level application for China Telecom’s online services, has allowed its development team to have close contact with TensorFlow and artificial intelligence (AI) technology. AI is an area that the Telecom Business Hall APP had never explored before, and even the engineers involved in the project transitioned from Android … Read more
Deep learning frameworks have played a crucial role in the rapid development in recent years, among which PyTorch and TensorFlow are the two most popular frameworks. They each have unique features and advantages, but there are also some similarities. This article will delve into PyTorch and TensorFlow, providing a detailed introduction from principles, code implementation, … Read more
This article was first published on WeChat public account: “The Beauty of Algorithms and Programming”, welcome to follow for more timely updates on this series of articles. Problem Description Here is an example of recognizing the mnist handwritten dataset. This dataset is a classic dataset in machine learning, consisting of 60k training samples and 10k … Read more
Author: Arjun Sarkar Translator: Chen Zhiyan Proofreader: Ouyang Jin This article is about 1900 words, and is recommended for an 8minute read. This article will teach you how to write custom loss functions using wrapper functions and OOP in Python. Tags: TensorFlow 2, Loss Function Figure 1: Gradient Descent Algorithm (Source: Public Domain, https://commons.wikimedia.org/w/index.php?curid=521422) Neural … Read more
In previous articles, we have introduced two types of image segmentation loss functions. Today, we will share commonly used multi-class image segmentation loss functions such as multi-class cross-entropy, weighted multi-class cross-entropy, multi-class Dice coefficient, multi-class Focal Loss, etc., and provide code to reproduce the above loss functions in TensorFlow. 1. Cross Entropy The cross-entropy loss … Read more
Click on the above“Beginner Learning Vision” to choose to addStar or “Pin” Important content delivered at the first time Introduction One of the most common uses of TensorFlow and Keras is image recognition/classification. Through this article, you will learn how to achieve this using Keras. Definition If you do not understand the basic concepts of … Read more
This article introduces how to build a simple neural network using Python 3.0 and TensorFlow 2.0 framework for basic image recognition. 1 Import Dataset from tensorflow import keras fashion_mnist = keras.datasets.fashion_mnist #devide the data into training and test: #train 60000 and test 10000 (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data() This code imports the MNIST image … Read more
From ｜jacobbuckman.com Author｜Jacob Buckman Compiled by｜Machine Heart (No Reposting), Xiaoshi Although for most people the development language of TensorFlow is Python, it is not a standard Python library. This neural network framework runs by constructing a “computation graph,” which can be quite confusing for many beginners trying to understand its logic. In this article, Jacob … Read more
This article contains 7196 words, and it is recommended to read in 10 minutes This article explains how to use TensorFlow for machine learning and deep learning. 1. Introduction The success of deep learning algorithms has led to groundbreaking advances in artificial intelligence research and applications, greatly changing our lives. More and more developers are … Read more
Original Title: An Introduction to PyTorch – A Simple yet Powerful Deep Learning Library Author: FAIZAN SHAIKH Translator: He Zhonghua This article is about 3600 words, recommended reading time is 15 minutes.This article will guide you step by step through PyTorch with practical examples. Introduction Every once in a while, a Python library emerges that … Read more