Course 2448
Course Introduction:If you have any questions, add WeChat: Le-studyg; in the course, we will first understand the background and characteristics of the PHP language, as well as the role and working principle of the PHP interpreter. Next, we will analyze the core components of the PHP interpreter in detail, such as lexical analysis, syntax analysis, virtual machine, etc., and gain an in-depth understanding of its internal implementation mechanism. In addition, the course will also introduce how to use C language to write various modules of the PHP interpreter, including lexical analyzer, syntax analyzer, virtual machine, etc. Through practical projects, students will personally implement a simple PHP interpreter and deepen their understanding of the PHP interpreter source code. Through the study of this course, students will be able to deeply understand the working principle and internal implementation mechanism of the PHP interpreter, and master the methods and techniques of writing PHP interpreters using C language. At the same time, students will also develop their ability to analyze and solve problems, and improve their programming skills and project practice capabilities. Whether you are a beginner who is interested in the PHP language or a developer who wants to have a deeper understanding of the internal mechanisms of the PHP interpreter, this course will provide you with valuable experience and inspiration. Let us explore the mysteries of the PHP interpreter and start the programming journey!
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.
Title: Achieve white text visibility on any color background except white
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Angular application without annotations
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2023-11-09 15:34:23 0 1 233
What are the performance numbers next to components in the Vue dev tools?
2023-11-09 14:46:48 0 1 305
Course Introduction:Model interpretability refers to the extent to which people can understand the decision rules and predicted results of a machine learning model. It involves understanding the model’s decision-making process and how the model makes predictions or classifications based on input data. Model interpretability is an important topic in the field of machine learning because it helps people understand the limitations, uncertainties, and potential biases of a model, thereby enhancing the trust and reliability of the model. By understanding the model's decision rules, people can better evaluate the model's performance in different situations and make decisions accordingly. In addition, model interpretability can help people discover errors or biases in the model and provide directions for improving the model. Therefore, improving the interpretability of models is of great significance to the application and development of machine learning. Here are some
2024-01-22 comment 0 580
Course Introduction:How to use PHP to build models Explanation and interpretability analysis Introduction: In the fields of machine learning and data science, building accurate models is only the first step. Understanding the interpretability of a model and how to interpret its results is critical to ensuring that the model is reliable and interpretable. In this article, we will explore how to build a model using PHP and analyze the interpretability of the model. 1. Model building Before starting, we need to ensure that PHP and related libraries have been installed. Before using PHP to build a model, we need to determine what
2023-07-31 comment 0 868
Course Introduction:可解释性AI(AI)是现代软件开发中不可或缺的一部分。将AI与Java框架集成提供了利用Java生态系统优势并构建具有解释能力的AI解决方案的途径。Java框架中常用的可解释性技术包括SHAP值、LIME和特征工程。本摘要使用SpringBootJava框架提供了一个实战案例,展示使用Xrai库进行模型预测和可解释性分析。通过集成Java框架与AI可解释性,开发者可以创建强大的、具有解释能力的AI模型,提高AI解决方案的可信度和可用性。
2024-06-08 comment 0 254
Course Introduction:The interpretability problem of machine learning models requires specific code examples. With the rapid development of machine learning and deep learning, more and more application scenarios use black box models, such as deep neural networks and support vector machines. These models have strong predictive performance in solving various problems, but their internal decision-making processes are difficult to explain and understand. This raises the issue of interpretability of machine learning models. The interpretability of a machine learning model refers to the ability to clearly and intuitively explain the decision-making basis and reasoning process of the model. In some application scenarios, we do not
2023-10-10 comment 0 484
Course Introduction:Go language has great advantages in building machine learning interpretability tools due to its high speed, concurrency and memory safety features. In a practical case, the LIME interpreter was built using Go, which can explain local model predictions. Its advantages include high performance, memory safety, and ease of use.
2024-05-08 comment 0 396