Course 48147
Course Introduction:Python is purely free software. The source code and interpreter CPython follow the GPL (GNU General Public License) agreement. The syntax is concise and clear, and one of its features is the forced use of white space as statement indentation. Has a rich and powerful library. It is often nicknamed the glue language, which can easily connect various modules made in other languages (especially C/C++) together.
Course 18880
Course Introduction:"JavaScript Learning Guide" will teach you to learn JavaScript knowledge from basic to advanced. Including syntax, variables, events, data types, loops, comparisons, objects, etc., allowing learners to have a cognitive process of JavaScript from elementary to advanced.
Course 2563
Course Introduction:This course is mainly a series of front-end development courses carefully created for students who are in the second stage of learning with zero foundation and want to enter the industry as front-end development. The course is based on the CRMEB open version, with practical drill teaching and a combination of theoretical explanation and practical operation. Better help students consolidate knowledge points and master operational skills. Effectively play the role of practical teaching to help students master development technologies.
Course 4901
Course Introduction:MongoDB is a general-purpose, document-based distributed database that helps modern application developers prepare for the cloud era. When it comes to databases, efficiency is a topic that never goes out of style.
WordPress 6.0 (add_editor_style) does not load style.css in Gutenberg editor
2023-11-12 20:37:50 0 2 261
How to bind v-model to methods in Vue.js
2023-11-05 16:36:26 0 1 193
LARAVEL8: Trying to access 'id' property on Null
2023-11-05 13:06:23 0 1 214
Why do so many JavaScript scripts append random numbers to things? collision?
2023-11-04 20:00:04 0 2 296
What is the difference between Nuxt and Vite?
2023-10-25 15:58:08 0 1 177
Course Introduction:Meta-learning helps machine learning algorithms overcome challenges by optimizing learning algorithms and identifying the best-performing algorithms. Meta-learning, meta-classifiers, and meta-regression Meta-classifiers in machine learning Meta-classifiers are a type of meta-learning algorithm in machine learning that are used for classification and predictive modeling tasks. It uses the results predicted by other classifiers as features and finally selects one of them as the final prediction result. Meta-regression Meta-regression is a meta-learning algorithm used for regression predictive modeling tasks. It uses regression analysis to combine, compare, and synthesize findings from several studies while adjusting for the effect of available covariates on the response variable. Meta-regression analyzes aim to reconcile conflicting studies or confirm studies that are consistent with each other. What techniques are used in meta-learning? Here are some methods used in meta-learning: Metrics
2024-01-24 comment 347
Course Introduction:Five must-learn libraries to help you learn Go language. As a simple and efficient programming language, Go language is becoming more and more popular among developers. In order to better learn and apply the Go language, it is essential to master some commonly used class libraries. This article will introduce the five must-learn class libraries, namely: fmt: The fmt class library is a standard library in the Go language for formatting input and output. Through this class library, various formatted outputs can be realized, such as printing variables, formatting strings, etc. Here is a simple example: packagema
2024-03-01 comment 875
Course Introduction:Zero-shot Learning (ZSL) is an emerging machine learning task whose goal is to classify unknown categories by learning the mapping relationship between known categories and unknown categories. Compared with traditional supervised learning tasks, zero-shot learning does not require obtaining unknown categories of data in advance during the training phase. It achieves classification of unknown categories by learning the semantic relationship between known categories and unknown categories, inferring the attributes of unknown categories and their positions in feature space. The advantage of this method is that it can handle unknown categories, giving the model better generalization capabilities. Zero-shot learning is a widely used technique, especially in the fields of natural language processing and computer vision. In natural language processing, zero times
2024-01-23 comment 0 483
Course Introduction:The machine learning classifier algorithm is an algorithm widely used in data mining, artificial intelligence and other fields. It can help solve practical problems by classifying and predicting data, and therefore plays an important role in modern artificial intelligence technology. Some commonly used machine learning classifier algorithms will be briefly introduced below. 1. Decision tree classifier Decision tree is a classifier based on a tree structure. It performs classification by dividing the data set into multiple subsets, where each subset corresponds to a node of the tree, ultimately forming a complete decision tree. During the classification process, the decision tree is traversed layer by layer according to the value of the feature until it reaches the leaf node, thereby obtaining the final classification result. Decision tree classifiers have the advantage of being easy to understand and interpret, but they are also prone to overfitting problems.
2024-01-24 comment 227
Course Introduction:Latent feature learning problem in unsupervised learning, requires specific code examples In the field of machine learning, unsupervised learning refers to the automatic learning and discovery of useful structures and patterns in data without label or category information. In unsupervised learning, latent feature learning is an important problem, which aims to learn higher-level, more abstract feature representations from raw input data. The goal of latent feature learning is to discover the most discriminating features from raw data to facilitate subsequent classification, clustering or other machine learning tasks. it can help
2023-10-08 comment 0 589