Common algorithm questions for front-end interviews in 2018
This time I bring you common algorithm questions for front-end interviews in 2018. What are the precautions for front-end interviews in 2018? Here are practical cases, let’s take a look.
[Related recommendations: Front-end interview questions(2020)]
1ObjectConvert to array
1 |
|
2. Statistics A stringThe most frequent letters
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 |
|
3. Find the maximum difference between the following positive arrays
1 2 3 4 5 6 |
|
4. Get the maximum or minimum value in the array
1 2 3 4 |
|
5. Generate a random alphanumeric string of specified length
1 2 |
|
I believe you have mastered the method after reading the case in this article. For more exciting information, please pay attention to the php Chinese websiteOthersrelated articles!
Related reading:
Tips on using jq to send multiple ajax and then execute callbacks
How to use pseudo-element first -letter capitalizes the first letter of the text
##Detailed explanation of JavaScript function overloading
The above is the detailed content of Common algorithm questions for front-end interviews in 2018. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Written above & the author’s personal understanding: At present, in the entire autonomous driving system, the perception module plays a vital role. The autonomous vehicle driving on the road can only obtain accurate perception results through the perception module. The downstream regulation and control module in the autonomous driving system makes timely and correct judgments and behavioral decisions. Currently, cars with autonomous driving functions are usually equipped with a variety of data information sensors including surround-view camera sensors, lidar sensors, and millimeter-wave radar sensors to collect information in different modalities to achieve accurate perception tasks. The BEV perception algorithm based on pure vision is favored by the industry because of its low hardware cost and easy deployment, and its output results can be easily applied to various downstream tasks.

Common challenges faced by machine learning algorithms in C++ include memory management, multi-threading, performance optimization, and maintainability. Solutions include using smart pointers, modern threading libraries, SIMD instructions and third-party libraries, as well as following coding style guidelines and using automation tools. Practical cases show how to use the Eigen library to implement linear regression algorithms, effectively manage memory and use high-performance matrix operations.

The bottom layer of the C++sort function uses merge sort, its complexity is O(nlogn), and provides different sorting algorithm choices, including quick sort, heap sort and stable sort.

01 Outlook Summary Currently, it is difficult to achieve an appropriate balance between detection efficiency and detection results. We have developed an enhanced YOLOv5 algorithm for target detection in high-resolution optical remote sensing images, using multi-layer feature pyramids, multi-detection head strategies and hybrid attention modules to improve the effect of the target detection network in optical remote sensing images. According to the SIMD data set, the mAP of the new algorithm is 2.2% better than YOLOv5 and 8.48% better than YOLOX, achieving a better balance between detection results and speed. 02 Background & Motivation With the rapid development of remote sensing technology, high-resolution optical remote sensing images have been used to describe many objects on the earth’s surface, including aircraft, cars, buildings, etc. Object detection in the interpretation of remote sensing images

The convergence of artificial intelligence (AI) and law enforcement opens up new possibilities for crime prevention and detection. The predictive capabilities of artificial intelligence are widely used in systems such as CrimeGPT (Crime Prediction Technology) to predict criminal activities. This article explores the potential of artificial intelligence in crime prediction, its current applications, the challenges it faces, and the possible ethical implications of the technology. Artificial Intelligence and Crime Prediction: The Basics CrimeGPT uses machine learning algorithms to analyze large data sets, identifying patterns that can predict where and when crimes are likely to occur. These data sets include historical crime statistics, demographic information, economic indicators, weather patterns, and more. By identifying trends that human analysts might miss, artificial intelligence can empower law enforcement agencies

1. Background of the Construction of 58 Portraits Platform First of all, I would like to share with you the background of the construction of the 58 Portrait Platform. 1. The traditional thinking of the traditional profiling platform is no longer enough. Building a user profiling platform relies on data warehouse modeling capabilities to integrate data from multiple business lines to build accurate user portraits; it also requires data mining to understand user behavior, interests and needs, and provide algorithms. side capabilities; finally, it also needs to have data platform capabilities to efficiently store, query and share user profile data and provide profile services. The main difference between a self-built business profiling platform and a middle-office profiling platform is that the self-built profiling platform serves a single business line and can be customized on demand; the mid-office platform serves multiple business lines, has complex modeling, and provides more general capabilities. 2.58 User portraits of the background of Zhongtai portrait construction

PHP algorithm analysis: An efficient method to find missing numbers in an array. In the process of developing PHP applications, we often encounter situations where we need to find missing numbers in an array. This situation is very common in data processing and algorithm design, so we need to master efficient search algorithms to solve this problem. This article will introduce an efficient method to find missing numbers in an array, and attach specific PHP code examples. Problem Description Suppose we have an array containing integers between 1 and 100, but one number is missing. We need to design a

As a new operating system launched by Huawei, Hongmeng system has caused quite a stir in the industry. As a new attempt by Huawei after the US ban, Hongmeng system has high hopes and expectations. Recently, I was fortunate enough to get a Huawei mobile phone equipped with Hongmeng system. After a period of use and actual testing, I will share some functional testing and usage experience of Hongmeng system. First, let’s take a look at the interface and functions of Hongmeng system. The Hongmeng system adopts Huawei's own design style as a whole, which is simple, clear and smooth in operation. On the desktop, various
