• Data types of PHP


    PHP has four and eight data types 1、 Scalar type Integer Floating point (floor) String Boolean (bloon) 2、 Complex type Array Object 3、 Special types NULL Resources 1  

  • New features of php7 (1)


    1. Scalar type declaration a) There are two modes of scalar type declaration: mandatory (default) and strict. You can now use the following type parameters (whether in mandatory or strict mode): string, int, float, and bool. They extend other types introduced in PHP 5: class name, interface, array and callback types. <?php // Coercive mode […]

  • Swift personal learning notes – 04: strings and characters


    This article is purely a Chinese version《The Swift Programming Language》So most of the content is in the article. This article is my study notes, not a formal and systematic record. For reference only There are still a lot of incomprehensible and uncertain points below, which I will point out with “doubtful” notes. Thanks to the […]

  • Strings / characters chat in swift3.0


    preface This article mainly analyzes the difference and simple usage of string characters between swift and Objective-C. If there is something wrong, I hope you can help correct it in time. String null In swift language, there are two ways to initialize empty string //Method 1: let testEmptyString0 = “” //Method 2: let testEmptyString1 = […]

  • Tensorflow learning – 1


    Tensorflow learning – 1   If life is just like seeing for the first time, what’s the matter with autumn wind.   Introduction:Tensorflow basic use, constant / variable, tensorflow 2.0 compatible with tensorflow 1.0. 1、 Code examples 1 import tensorflow as tf 2 3 print(“tensorFlow version is: ” + tf.__version__) 4 5 # create two […]

  • [pytorch learning notes] 1.2 introduction to tensor


    thumbnail: https://image.zhangxiann.com/…toc: truedate: 2020/2/5 20:39:20disqusId: zhangxiancategories: PyTorch tags: AI Deep Learning Code of this chapter: https://github.com/zhangxiann/PyTorch_Practice/blob/master/lesson1/tensor_introduce1.py https://github.com/zhangxiann/PyTorch_Practice/blob/master/lesson1/tensor_introduce1.py The concept of tensor Tensor is tensor in Chinese. Tensor means a multidimensional array, which is a high-dimensional extension of scalar, vector and matrix. Scalar can be called 0-dimensional tensor, vector can be called 1-dimensional tensor, matrix can […]

  • SQL server queries stored procedures or attempts based on table names


    Select a.name source name, b.text code content, case When a. xtype’v ‘then’ view ‘ When a.xtype’p ‘then’ stored procedure ‘ When a. xtype = FN ‘then’ scalar function ‘ When a.xtype = TF ‘then’ table function ‘ When a.xtype = tr ‘then’ trigger ‘ else a.xtype End type from sysobjects a inner join syscomments b […]

  • Tikv source code analysis series (15) expression calculation framework


    Author: Luo Dean The last article “tikv source code analysis series (XIV) coprocessor Overview” mentioned that in order to maximize the use of distributed computing power, tidb will try to push down the selection operator and aggregation operator to the tikv node. This article will continue to introduce the source code architecture of expression calculation […]

  • MemCache


    1、 Introduction of Memcache 1. Basic concepts of memcached (1) Memcached is a project of danga. It was originally developed by livejournal service to accelerate the access speed of livejournal. Later, it was adopted by many large websites. Official website: www.danga.com And http://memcached.org (2) Memcached is a high-performance distributed memory object caching system, It is […]

  • 30 minutes to understand the core concepts of graphql


    Write in front In the last article RPC vs rest vs graphql, we made a macro comparison of the advantages and disadvantages of the three. Moreover, we will find that generally simple projects do not need graphql, but we still need to have a certain understanding and mastery of the new technology, so we will […]

  • Tikv source code analysis series article (15) expression calculation framework


    By Luo Dean In the previous “tikv source code analysis series article (XIV) coprocessor Overview”, it was mentioned that in order to maximize the use of distributed computing capacity, tidb will try to push down the selection operator, aggregation operator and other operators to the tikv node. This article will continue to introduce the source […]

  • Machine learning notes (1)


      1、 Supervised learning and unsupervised learning   1. In supervised learning, data set is composed of feature group and tag, which aims to train the machine to accurately predict tag value. Such as: house price prediction, tumor determination, spam determination. 2. In unsupervised learning, no manual explanation, no answer and no label are given […]