• PHP real regular expression (2): extracting HTML elements


    This article introduces how to extract HTML elements from regular expressionspattern modifier 、Greedy matchingAndNon greedy matching、Unicode mode、Look aroundAnd so on.Before reading this article, it’s better to read the same series of articlesPHP real regular expression (1): verifying mobile phone numberRead it carefully first. Basic extraction There is such a form user name occupation Kobe Bryant […]

  • Basic knowledge of regular expressions (PHP)


    The knowledge points here are basically the reading notes of the regular guide, but the sample code of each knowledge point is implemented in PHP. 1. Character group Character class is a group of characters. In regular expressions, it means “all kinds of characters that may appear in the same position”.Writing: [AB], [314], [#.?] Basic […]

  • Overview of countermeasure verification


    Learn how to implement adversarial verification to build classifiers to determine whether your data comes from a training or test set. If you can, there is a problem with your data, and the adversary validation model can help you diagnose the problem. If you’re looking at some winning solutions on kaggle, you might notice a […]

  • Introduction to regularization


    I’ve seen many regular tutorials before, but I don’t receive much. I just skim the water and pass by a little bit. In fact, regularization is extremely useful, such as matching innerHTML content and form validation. Here, I combine JS to give a brief introduction to regularization. If there are any mistakes, please point them […]

  • Swiss Army knife — regular expression


    brief introduction Regular expression, also known as regular expression, regular expression, regular expression (English: regular expression, often abbreviated as regex, regexp or re in code), is a concept of computer science. Regular expressions use a single string to describe and match a series of strings that conform to a certain syntactic rule. In many text […]

  • Auc-roc curve in machine learning


    By aniruddha BhandariCompile | VKSource: analytics vidhya Auc-roc curve You’ve built your machine learning model – so what’s next? You need to evaluate it and verify how good (or bad) it is so that you can decide whether to implement it or not. At this point, the auc-roc curve can be introduced. The name may […]

  • Fake news is everywhere: I created an open source project to mark fake news through deep learning


    The rise of fake news has forced everyone with a social media account to become a detective, responsible for determining whether a post is genuine before it is published. However, false news will still cross our defense line and spread rapidly on the network, which is aggravated by the ignorance and carelessness of users. As […]

  • What is transfer learning? (with tensorflow code implementation)


    1、 The concept of transfer learning What is transfer learning? Transfer learning can be represented by the following diagram:     The leftmost part of this graph shows the transfer learning, that is, the trained model and weight are directly incorporated into the new dataset for training, but we only change the classifier of the […]

  • Spark NLP text classification based on Bert and general sentence coding


    By veysel kocamanCompile | VKSource: toward Data Science Natural language processing (NLP) is a key component of many data science systems that must understand or reason text. Common use cases include text classification, question answering, interpretation or summary, sentiment analysis, natural language Bi, language modeling and disambiguation. NLP is becoming more and more important in […]

  • Learning JavaScript regular expressions


    1、 How to create regular expressions 1. Literal quantity or direct quantity (it is not necessary to use any key words to indicate that it is a regular expression, but a slash is used to indicate the beginning and end of a regular expression) eg: var reg = /^\w/; 2. Object eg: var reg = […]

  • Regular expression memo (recommended Collection)


    Anchor point ^: the beginning of a string or the beginning of a row in multiline mode $: end of string or end of line in multiline mode \b: word boundary \B: is not a word boundary\b) Note: the anchor is not quantifiable (i.e., there can be no quantifier after it). Character sequence .: any […]

  • 4. Bagging and boosting


    Bagging and boosting Two representative works of ensemble learning 1.Bagging Algorithm process: different training samples are obtained by resampling the training samples, and K training sets are obtained (k training sets are independent of each other); K models are obtained by training each training set; the classification problem adopts votes method, and the regression model […]