Home Operation and Maintenance Windows Operation and Maintenance How to perform relevant configurations during the installation of dual systems

How to perform relevant configurations during the installation of dual systems

Sep 15, 2018 pm 04:49 PM
machine learning deep learning

The content of this article is about how to perform relevant configurations during the installation of dual systems. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

After this week of tossing, I will record my own related configuration experience to share with you. Initially, I installed Ubuntu and Centos in VMware, but I found that the local GPU cannot be used in the virtual machine. Later, deep learning requires the help of the GPU, and only using the CPU will be very slow. It just so happens that during this period of time, I first learned Linux on a virtual machine, and then I will feel comfortable installing dual systems during this period.

Step one to install dual systems:

Available: ubuntu-16.04-desktop-amd64.iso system image, one USB disk, burn System to U disk tool UltraISO, set up the boot tool easyBCD

My original win10 system is an SSD on the c drive, and I opened up a space of about 100g for Ubuntu, and used the U disk to install it. I just installed Ubuntu14.04 , but it may be a problem with my ios image. After installation, there is no wireless driver, no wlan0, and it needs to be updated. What’s really annoying is the client that needs to be logged in to the school’s wired network. There is another problem when installing wine, so I just go to it directly. My classmate installed the latest Ubuntu 16.04, and finally the installation was successful without any problems.

How to perform relevant configurations during the installation of dual systems

#1. Of course, this step during the installation process depends on the situation. Generally, if you are not connected to the network, you do not need to choose to install third-party software, just click to continue.

How to perform relevant configurations during the installation of dual systems

2. This step is very important. Remember to click on other options. Many people have lost their original Windows system. You just chose the first one, right?

How to perform relevant configurations during the installation of dual systems

3.When assigning a drive letter, select the free disk disk and click

First set the swap swap partition. The type of the new partition: logical partition

The location of the new partition: the starting position of the space,

is used for: swap space, which is considered to be twice the physical memory on the Internet. In fact, 2g is enough. I allocated 8g

to set up the boot partition. This is used to set up the startup boot. Size: 200MB (the author temporarily sets it to 200MB)

Type of new partition: logical partition

Location of new partition: space starting position

Used for: EXT4 log file System

Set the "/" root partition, many default system applications will be installed here later

Size: as large as possible

Type of new partition: primary partition

The location of the new partition: the starting position of the space

Used for: EXT4 log file system

Set the /home partition, which is equivalent to storing your own things, somewhat similar to that under win d, e, f disk

Size: (All remaining space, as much as shown)

Type of new partition: logical partition

Location of the new partition : Space starting position

Used for: EXT4 log file system

It is very important to remember to select /bootThe corresponding drive letter is "the device to install the bootloader", be sure to be consistent:

4. Pay attention to the beginning and end of the installation process. One is to remember to turn off secure boot in advanced startup. I then restarted the computer directly and entered bios to turn it off. There was a problem (anyway, I This is true); remember to set up the boot after the installation is completed, otherwise you will still directly enter the win10 system every time you turn on the computer. Tip: It is best to choose newer versions of easybcd and UltraISO. Some of the direct searches on the Internet may be older versions, and some may cause problems.

The above is the detailed content of How to perform relevant configurations during the installation of dual systems. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

This article will take you to understand SHAP: model explanation for machine learning This article will take you to understand SHAP: model explanation for machine learning Jun 01, 2024 am 10:58 AM

In the fields of machine learning and data science, model interpretability has always been a focus of researchers and practitioners. With the widespread application of complex models such as deep learning and ensemble methods, understanding the model's decision-making process has become particularly important. Explainable AI|XAI helps build trust and confidence in machine learning models by increasing the transparency of the model. Improving model transparency can be achieved through methods such as the widespread use of multiple complex models, as well as the decision-making processes used to explain the models. These methods include feature importance analysis, model prediction interval estimation, local interpretability algorithms, etc. Feature importance analysis can explain the decision-making process of a model by evaluating the degree of influence of the model on the input features. Model prediction interval estimate

Identify overfitting and underfitting through learning curves Identify overfitting and underfitting through learning curves Apr 29, 2024 pm 06:50 PM

This article will introduce how to effectively identify overfitting and underfitting in machine learning models through learning curves. Underfitting and overfitting 1. Overfitting If a model is overtrained on the data so that it learns noise from it, then the model is said to be overfitting. An overfitted model learns every example so perfectly that it will misclassify an unseen/new example. For an overfitted model, we will get a perfect/near-perfect training set score and a terrible validation set/test score. Slightly modified: "Cause of overfitting: Use a complex model to solve a simple problem and extract noise from the data. Because a small data set as a training set may not represent the correct representation of all data." 2. Underfitting Heru

Beyond ORB-SLAM3! SL-SLAM: Low light, severe jitter and weak texture scenes are all handled Beyond ORB-SLAM3! SL-SLAM: Low light, severe jitter and weak texture scenes are all handled May 30, 2024 am 09:35 AM

Written previously, today we discuss how deep learning technology can improve the performance of vision-based SLAM (simultaneous localization and mapping) in complex environments. By combining deep feature extraction and depth matching methods, here we introduce a versatile hybrid visual SLAM system designed to improve adaptation in challenging scenarios such as low-light conditions, dynamic lighting, weakly textured areas, and severe jitter. sex. Our system supports multiple modes, including extended monocular, stereo, monocular-inertial, and stereo-inertial configurations. In addition, it also analyzes how to combine visual SLAM with deep learning methods to inspire other research. Through extensive experiments on public datasets and self-sampled data, we demonstrate the superiority of SL-SLAM in terms of positioning accuracy and tracking robustness.

The evolution of artificial intelligence in space exploration and human settlement engineering The evolution of artificial intelligence in space exploration and human settlement engineering Apr 29, 2024 pm 03:25 PM

In the 1950s, artificial intelligence (AI) was born. That's when researchers discovered that machines could perform human-like tasks, such as thinking. Later, in the 1960s, the U.S. Department of Defense funded artificial intelligence and established laboratories for further development. Researchers are finding applications for artificial intelligence in many areas, such as space exploration and survival in extreme environments. Space exploration is the study of the universe, which covers the entire universe beyond the earth. Space is classified as an extreme environment because its conditions are different from those on Earth. To survive in space, many factors must be considered and precautions must be taken. Scientists and researchers believe that exploring space and understanding the current state of everything can help understand how the universe works and prepare for potential environmental crises

Implementing Machine Learning Algorithms in C++: Common Challenges and Solutions Implementing Machine Learning Algorithms in C++: Common Challenges and Solutions Jun 03, 2024 pm 01:25 PM

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.

Five schools of machine learning you don't know about Five schools of machine learning you don't know about Jun 05, 2024 pm 08:51 PM

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

Explainable AI: Explaining complex AI/ML models Explainable AI: Explaining complex AI/ML models Jun 03, 2024 pm 10:08 PM

Translator | Reviewed by Li Rui | Chonglou Artificial intelligence (AI) and machine learning (ML) models are becoming increasingly complex today, and the output produced by these models is a black box – unable to be explained to stakeholders. Explainable AI (XAI) aims to solve this problem by enabling stakeholders to understand how these models work, ensuring they understand how these models actually make decisions, and ensuring transparency in AI systems, Trust and accountability to address this issue. This article explores various explainable artificial intelligence (XAI) techniques to illustrate their underlying principles. Several reasons why explainable AI is crucial Trust and transparency: For AI systems to be widely accepted and trusted, users need to understand how decisions are made

Is Flash Attention stable? Meta and Harvard found that their model weight deviations fluctuated by orders of magnitude Is Flash Attention stable? Meta and Harvard found that their model weight deviations fluctuated by orders of magnitude May 30, 2024 pm 01:24 PM

MetaFAIR teamed up with Harvard to provide a new research framework for optimizing the data bias generated when large-scale machine learning is performed. It is known that the training of large language models often takes months and uses hundreds or even thousands of GPUs. Taking the LLaMA270B model as an example, its training requires a total of 1,720,320 GPU hours. Training large models presents unique systemic challenges due to the scale and complexity of these workloads. Recently, many institutions have reported instability in the training process when training SOTA generative AI models. They usually appear in the form of loss spikes. For example, Google's PaLM model experienced up to 20 loss spikes during the training process. Numerical bias is the root cause of this training inaccuracy,

See all articles