Course 2857
Course Introduction:Course introduction: 1. Cross-domain processing, token management, route interception; 2. Real interface debugging, API layer encapsulation; 3. Secondary encapsulation of Echarts and paging components; 4. Vue packaging optimization and answers to common problems.
Course 1795
Course Introduction:Apipost is an API R&D collaboration platform that integrates API design, API debugging, API documentation, and automated testing. It supports grpc, http, websocket, socketio, and socketjs type interface debugging, and supports privatized deployment. Before formally learning ApiPost, you must understand some related concepts, development models, and professional terminology. Apipost official website: https://www.apipost.cn
Course 5521
Course Introduction:(Consult WeChat: phpcn01) The comprehensive practical course aims to consolidate the learning results of the first two stages, achieve flexible application of front-end and PHP core knowledge points, complete your own projects through practical training, and provide guidance on online implementation. Comprehensive practical key practical courses include: social e-commerce system backend development, product management, payment/order management, customer management, distribution/coupon system design, the entire WeChat/Alipay payment process, Alibaba Cloud/Pagoda operation and maintenance, and project online operation. .....
Course 5172
Course Introduction:(Consult WeChat: phpcn01) Starting from scratch, you can solve conventional business logic, operate MySQL with PHP to add, delete, modify, and query, display dynamic website data, master the MVC framework, master the basics of the ThinkPHP6 framework, and learn and flexibly master all knowledge involved in PHP development. point.
Course 8713
Course Introduction:(Consult WeChat: phpcn01) The learning objectives of the front-end development part of the 22nd issue of PHP Chinese website: 1. HTML5/CSS3; 2. JavaScript/ES6; 3. Node basics; 4. Vue3 basics and advanced; 5. Mobile mall/ Website background homepage layout; 6. Automatic calculation of tabs/carousels/shopping carts...
Why do some mysql connections select old data of mysql database after delete+insert?
2023-10-30 12:37:20 0 2 229
Why can't void and {} be inferred as never type in TypeScript?
2023-09-04 16:03:52 0 1 294
Can I use OAuth 2.0 without a redirect server?
2023-08-22 22:18:09 0 2 283
IntersectionObserver's callback function was not called
2023-08-15 20:15:03 0 1 182
Course Introduction:The difference between a crossover cable and a direct connection cable is: 1. A direct connection cable uses the same wire sequence at both ends of the same network cable, either 568A standard or 568B standard, while a crossover cable is the same network cable The two sections use different line sequences; 2. Straight-through cables are used to connect computers to switches and routers, while crossover cables are used to connect computers to computers.
2020-09-03 comment 0 41148
Course Introduction:Machine learning and deep learning models are commonly used to solve regression and classification problems. In supervised learning, the model learns during training how to map inputs to probabilistic outputs. In order to optimize the performance of the model, a loss function is often used to evaluate the difference between the predicted results and the true labels, among which cross-entropy is a common loss function. It measures the difference between the probability distribution predicted by the model and the true labels. By minimizing the cross-entropy, the model can predict the output more accurately. What is Cross Entropy? Cross entropy is a measure of the difference between two probability distributions for a given set of random variables or events. Cross entropy is a commonly used loss function, mainly used to optimize classification models. The performance of the model can be measured by the value of the loss function. The lower the loss, the better the model. cross entropy loss
2024-01-22 comment 0 616
Course Introduction:In machine learning tasks, the loss function is an important indicator for evaluating model performance and is used to measure the difference between the model's prediction results and the real results. Cross-entropy is a common loss function widely used in classification problems. It measures a model's accuracy by calculating the difference between the model's predictions and the true results. Sparse cross-entropy is an extended form of cross-entropy and is mainly used to solve class imbalance in classification problems. When choosing a loss function, you need to consider the characteristics of the data set and the goals of the model. Cross entropy is suitable for general classification problems, while sparse cross entropy is more suitable for dealing with class imbalance. Choosing an appropriate loss function can improve the performance and generalization ability of the model, thereby improving the effectiveness of machine learning tasks. 1. Cross entropy Cross entropy is a classification problem
2024-01-22 comment 782
Course Introduction:With the development of cloud computing, more and more applications need to run across platforms. Golang, as a strongly typed language, also performs well in this field. Cross-compilation is the process of compiling source code in one platform environment and running it on another platform. This article will introduce the cross-compilation process of Golang. Cross-compilation process First, you need to download the cross-compilation tool chain. On the official website of Golang, we can find the download link corresponding to the platform, as shown in the figure below:![Screenshot of golang download page](htt
2023-05-10 comment 0 531
Course Introduction:Make several intersecting images, one completely overlapping the large circle and two with intersecting parts. Select the small square that completely overlaps and contains it. Right-click and select the fill color blue. This tutorial is shared by Computer Expert Network. Left-click and select the edge color black. Select smart fill. Select the fill color and border color. Use the mouse to click on the intersecting square to get two new ones. of
2024-05-08 comment 423