Course 2672
Course Introduction:Golang has an in-depth understanding of the GPM scheduler model and full scenario analysis. I hope you will gain something from watching this video; it includes the origin and analysis of the scheduler, an introduction to the GMP model, and a summary of 11 scenarios.
Course 5963
Course Introduction:The flex property is used to set or retrieve how the child elements of the flex box model object allocate space. It is the shorthand property for the flex-grow, flex-shrink and flex-basis properties. Note: The flex property has no effect if the element is not a child of the flexbox model object.
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. .....
2023-11-17 08:50:36 0 0 84
2023-11-14 12:58:58 0 1 292
Indirect modification of the overloaded attribute of App\Models\User::$profile is invalid.
2023-11-08 11:50:44 0 1 270
CSS collapsing margins: what is their purpose?
2023-10-25 19:38:51 0 1 221
Error in Laravel 5.3: Field has no default value
2023-10-22 19:57:57 0 1 213
Course Introduction:本站5月15日消息,今天上午,字节跳动在2024春季火山引擎Force原动力大会上正式宣布自家豆包大模型正式开启对外服务。据介绍,豆包大模型包含豆包通用模型Pro、豆包通用模型liti、豆包・角色扮演模型、豆包・语音合成模型、豆包・声音复刻模型、豆包・语音识别模型、豆包・文生图模型、豆包・FunctionCall模型。官方表示,此次大会共分为“AI增长焕新机、AI应用新范式、AI算力强护航”三个篇章。除发布字节跳动自研大模型外,字节跳动还宣布火山引擎大模型服务平台——火山方舟也将迎来重大升级。同时,字节跳
2024-05-15 comment 837
Course Introduction:Model distillation and pruning are neural network model compression technologies that effectively reduce parameters and computational complexity, and improve operating efficiency and performance. Model distillation improves performance by training a smaller model on a larger model, transferring knowledge. Pruning reduces model size by removing redundant connections and parameters. These two techniques are very useful for model compression and optimization. Model Distillation Model distillation is a technique that replicates the predictive power of a large model by training a smaller model. The large model is called the "teacher model" and the small model is called the "student model". Teacher models typically have more parameters and complexity and are therefore better able to fit the training and test data. In model distillation, the student model is trained to imitate the predicted behavior of the teacher model to achieve better performance on a smaller model.
2024-01-23 comment 299
Course Introduction:Large language models and word embedding models are two key concepts in natural language processing. They can both be applied to text analysis and generation, but the principles and application scenarios are different. Large-scale language models are mainly based on statistical and probabilistic models and are suitable for generating continuous text and semantic understanding. The word embedding model can capture the semantic relationship between words by mapping words to vector space, and is suitable for word meaning inference and text classification. 1. Word embedding model The word embedding model is a technology that processes text information by mapping words into a low-dimensional vector space. It converts words in a language into vector form so that computers can better understand and process text. Commonly used word embedding models include Word2Vec and GloVe. These models are widely used in natural language processing tasks
2024-01-23 comment 965
Course Introduction:Classification models can be divided into two categories: generative models and discriminative models. This article explains the differences between these two model types and discusses the pros and cons of each approach. Discriminative model A discriminative model is a model that can learn the relationship between input data and output labels. It predicts the output labels by learning the characteristics of the input data. In a classification problem, our goal is to assign each input vector x to a label y. Discriminative models attempt to directly learn a function f(x) that maps input vectors to labels. These models can be further divided into two subtypes: Classifiers try to find f(x) without using any probability distribution. These classifiers directly output a label for each sample without providing a probability estimate of the class. These classifiers are often called deterministic classifiers or
2023-05-19 comment 0 601
Course Introduction:With the rapid development of artificial intelligence, the complexity of models is getting higher and higher, and the use of resources is also increasing. In PHP, how to perform model fusion and model compression has become a hot topic. Model fusion refers to fusing multiple single models together to improve overall accuracy and efficiency. Model compression reduces the size and computational complexity of the model to save model storage and computing resources. This article will introduce how to perform model fusion and model compression in PHP. 1. Model fusion In PHP, there are two commonly used model fusion methods:
2023-05-23 comment 0 950