python入门概念_带有Python的AI –入门概念

╰半夏微凉° 2022-12-10 01:27 358阅读 0赞

![python入门概念][python]

python入门概念

# 带有Python的AI –入门概念 **(**AI with Python – Primer Concept**)** #

Since the invention of computers or machines, their capability to perform various tasks has experienced an exponential growth. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time.

自从计算机或机器发明以来，它们执行各种任务的能力经历了指数级增长。 人们已经在计算机系统的各种工作领域，其不断提高的速度以及相对于时间的减小方面开发了强大的计算机系统。

A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.

计算机科学的一个分支，叫做人工智能，致力于创造像人类一样智能的计算机或机器。

## 人工智能(AI)的基本概念 **(**Basic Concept of Artificial Intelligence (AI)**)** ##

According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”.

人工智能之父约翰·麦卡锡(John McCarthy)说，这是“制造智能机器，尤其是智能计算机程序的科学和工程学”。

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think. AI is accomplished by studying how human brain thinks and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.

人工智能是一种使计算机，计算机控制的机器人或软件进行智能思考的方式，类似于智能人类的思考方式。 通过研究人脑在解决问题时的思维方式以及学习，决定和工作的方式，然后将本研究的结果作为开发智能软件和系统的基础，可以实现AI。

While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, “Can a machine think and behave like humans do?”

在利用计算机系统的功能时，人类的好奇心使他想知道：“一台机器能像人类一样思考和行为吗？”

Thus, the development of AI started with the intention of creating similar intelligence in machines that we find and regard high in humans.

因此，人工智能的发展始于在我们发现并视为人类崇高的机器中创建类似智能的意图。

## 学习AI的必要性 **(**The Necessity of Learning AI**)** ##

As we know that AI pursues creating the machines as intelligent as human beings. There are numerous reasons for us to study AI. The reasons are as follows −

众所周知，人工智能致力于创造与人类一样智能的机器。 我们学习AI的原因很多。 原因如下-

### 人工智能可以通过数据学习 **(**AI can learn through data**)** ###

In our daily life, we deal with huge amount of data and human brain cannot keep track of so much data. That is why we need to automate the things. For doing automation, we need to study AI because it can learn from data and can do the repetitive tasks with accuracy and without tiredness.

在我们的日常生活中，我们处理大量数据，而人脑无法跟踪那么多数据。 这就是为什么我们需要使事情自动化。 为了实现自动化，我们需要研究AI，因为它可以从数据中学习，并且可以准确而又轻松地完成重复性任务。

### 人工智能可以自学 **(**AI can teach itself**)** ###

It is very necessary that a system should teach itself because the data itself keeps changing and the knowledge which is derived from such data must be updated constantly. We can use AI to fulfill this purpose because an AI enabled system can teach itself.

系统必须自学，因为数据本身不断变化，并且必须不断更新从这些数据中获得的知识。 我们可以使用AI来实现此目的，因为启用AI的系统可以自学。

### 人工智能可以实时响应 **(**AI can respond in real time**)** ###

Artificial intelligence with the help of neural networks can analyze the data more deeply. Due to this capability, AI can think and respond to the situations which are based on the conditions in real time.

借助神经网络的人工智能可以更深入地分析数据。 由于此功能，AI可以根据条件实时思考和响应情况。

### 人工智能实现准确性 **(**AI achieves accuracy**)** ###

With the help of deep neural networks, AI can achieve tremendous accuracy. AI helps in the field of medicine to diagnose diseases such as cancer from the MRIs of patients.

借助深度神经网络，人工智能可以实现巨大的准确性。 AI在医学领域帮助从患者的MRI诊断癌症等疾病。

### 人工智能可以组织数据以充分利用数据 **(**AI can organize data to get most out of it**)** ###

The data is an intellectual property for the systems which are using self-learning algorithms. We need AI to index and organize the data in a way that it always gives the best results.

数据是使用自学习算法的系统的知识产权。 我们需要AI以始终提供最佳结果的方式来索引和组织数据。

### 了解情报 **(**Understanding Intelligence**)** ###

With AI, smart systems can be built. We need to understand the concept of intelligence so that our brain can construct another intelligence system like itself.

借助AI，可以构建智能系统。 我们需要了解智能的概念，以便我们的大脑可以像自己一样构造另一个智能系统。

## 什么是智力？ **(**What is Intelligence?**)** ##

The ability of a system to calculate, reason, perceive relationships and analogies, learn from experience, store and retrieve information from memory, solve problems, comprehend complex ideas, use natural language fluently, classify, generalize, and adapt new situations.

系统具有计算，推理，感知关系和类比，从经验中学习，从内存中存储和检索信息，解决问题，理解复杂思想，流利使用自然语言，分类，概括和适应新情况的能力。

### 智力类型 **(**Types of Intelligence**)** ###

As described by Howard Gardner, an American developmental psychologist, Intelligence comes in multifold −

正如美国发展心理学家霍华德·加德纳(Howard Gardner)所描述的，智力具有多重性-

<table> 
 <tbody> 
 <tr> 
 <th>Sr.No</th> 
 <th>Intelligence &amp; Description</th> 
 <th>Example</th> 
 </tr> 
 <tr> 
 <td>1</td> 
 <td>Linguistic intelligence The ability to speak, recognize, and use mechanisms of phonology (speech sounds), syntax (grammar), and semantics (meaning).</td> 
 <td>Narrators, Orators</td> 
 </tr> 
 <tr> 
 <td>2</td> 
 <td>Musical intelligence The ability to create, communicate with, and understand meanings made of sound, understanding of pitch, rhythm.</td> 
 <td>Musicians, Singers, Composers</td> 
 </tr> 
 <tr> 
 <td>3</td> 
 <td>Logical-mathematical intelligence The ability to use and understand relationships in the absence of action or objects. It is also the ability to understand complex and abstract ideas.</td> 
 <td>Mathematicians, Scientists</td> 
 </tr> 
 <tr> 
 <td>4</td> 
 <td>Spatial intelligence The ability to perceive visual or spatial information, change it, and re-create visual images without reference to the objects, construct 3D images, and to move and rotate them.</td> 
 <td>Map readers, Astronauts, Physicists</td> 
 </tr> 
 <tr> 
 <td>5</td> 
 <td>Bodily-Kinesthetic intelligence The ability to use complete or part of the body to solve problems or fashion products, control over fine and coarse motor skills, and manipulate the objects.</td> 
 <td>Players, Dancers</td> 
 </tr> 
 <tr> 
 <td>6</td> 
 <td>Intra-personal intelligence The ability to distinguish among one’s own feelings, intentions, and motivations.</td> 
 <td>Gautam Buddhha</td> 
 </tr> 
 <tr> 
 <td>7</td> 
 <td>Interpersonal intelligence The ability to recognize and make distinctions among other people’s feelings, beliefs, and intentions.</td> 
 <td>Mass Communicators, Interviewers</td> 
 </tr> 
 </tbody> 
</table>

<table> 
 <tbody> 
 <tr> 
 <th> 序号 </th> 
 <th> 情报与描述 </th> 
 <th> 例 </th> 
 </tr> 
 <tr> 
 <td> 1个 </td> 
 <td> 语言智能 语音，识别和使用语音学(语音)，语法(语法)和语义(含义)机制的能力。 </td> 
 <td> 叙述者，演说家 </td> 
 </tr> 
 <tr> 
 <td> 2 </td> 
 <td> 音乐智力 创造，交流和理解声音含义，理解音调，节奏的能力。 </td> 
 <td> 音乐家，歌手，作曲家 </td> 
 </tr> 
 <tr> 
 <td> 3 </td> 
 <td> 逻辑数学智能 在没有动作或物体的情况下使用和理解关系的能力。 它也是理解复杂抽象概念的能力。 </td> 
 <td> 数学家，科学家 </td> 
 </tr> 
 <tr> 
 <td> 4 </td> 
 <td> 空间情报 感知视觉或空间信息，对其进行更改并重新创建视觉图像而无需参考对象，构建3D图像以及移动和旋转它们的能力。 </td> 
 <td> 地图阅读器，宇航员，物理学家 </td> 
 </tr> 
 <tr> 
 <td> 5 </td> 
 <td> 身体运动智能 使用身体的全部或一部分来解决问题或时尚产品，控制精细和粗略运动技能以及操纵对象的能力。 </td> 
 <td> 选手，舞者 </td> 
 </tr> 
 <tr> 
 <td> 6 </td> 
 <td> 人际智能 区分自己的感觉，意图和动机的能力。 </td> 
 <td> 高塔姆佛 </td> 
 </tr> 
 <tr> 
 <td> 7 </td> 
 <td> 人际关系智能 识别并区分其他人的感觉，信念和意图的能力。 </td> 
 <td> 大众传播者，访问者 </td> 
 </tr> 
 </tbody> 
</table>

You can say a machine or a system is artificially intelligent when it is equipped with at least one or all intelligences in it.

您可以说机器或系统中装有至少一个或所有智能设备时，便是人工智能。

## 什么是情报？ **(**What is Intelligence Composed Of?**)** ##

The intelligence is intangible. It is composed of −

智力是无形的。 它由-组成

*  Reasoning
    
    推理
 *  Learning
    
    学习
 *  Problem Solving
    
    解决问题
 *  Perception
    
    知觉
 *  Linguistic Intelligence
    
    语言智能

![Intelligence][]

Let us go through all the components briefly −

让我们简要介绍所有组件-

### 推理 **(**Reasoning**)** ###

It is the set of processes that enable us to provide basis for judgement, making decisions, and prediction. There are broadly two types −

这是一组过程，使我们能够为判断，决策和预测提供基础。 大致有两种类型-

<table> 
 <tbody> 
 <tr> 
 <th>Inductive Reasoning</th> 
 <th>Deductive Reasoning</th> 
 </tr> 
 <tr> 
 <td>It conducts specific observations to makes broad general statements.</td> 
 <td>It starts with a general statement and examines the possibilities to reach a specific, logical conclusion.</td> 
 </tr> 
 <tr> 
 <td>Even if all of the premises are true in a statement, inductive reasoning allows for the conclusion to be false.</td> 
 <td>If something is true of a class of things in general, it is also true for all members of that class.</td> 
 </tr> 
 <tr> 
 <td>Example − "Nita is a teacher. Nita is studious. Therefore, All teachers are studious."</td> 
 <td>Example − "All women of age above 60 years are grandmothers. Shalini is 65 years. Therefore, Shalini is a grandmother."</td> 
 </tr> 
 </tbody> 
</table>

<table> 
 <tbody> 
 <tr> 
 <th> 归纳推理 </th> 
 <th> 演绎推理 </th> 
 </tr> 
 <tr> 
 <td> 它进行特定的观察以做出广泛的一般性陈述。 </td> 
 <td> 它从一般性陈述开始，并检验得出具体，合乎逻辑的结论的可能性。 </td> 
 </tr> 
 <tr> 
 <td> 即使陈述中的所有前提都是正确的，归纳推理也可以使结论是错误的。 </td> 
 <td> 如果某类事物总体上是正确的，则该类的所有成员也都正确。 </td> 
 </tr> 
 <tr> 
 <td> 示例 -“ Nita是一名教师。Nita是一名勤奋的学生。因此，所有老师都是勤奋的学生。” </td> 
 <td> 示例 -“所有60岁以上的女性都是祖母。Shalini是65岁。因此，Shalini是祖母。” </td> 
 </tr> 
 </tbody> 
</table>

## 学习-l **(**Learning − l**)** ##

The ability of learning is possessed by humans, particular species of animals, and AI-enabled systems. Learning is categorized as follows −

人类，特定种类的动物以及支持AI的系统具有学习的能力。 学习分类如下-

### 听觉学习 **(**Auditory Learning**)** ###

It is learning by listening and hearing. For example, students listening to recorded audio lectures.

它是通过听和听来学习。 例如，学生听录制的音频讲座。

### 情景学习 **(**Episodic Learning**)** ###

To learn by remembering sequences of events that one has witnessed or experienced. This is linear and orderly.

通过记住一个人亲眼目睹或经历过的事件序列来学习。 这是线性且有序的。

### 运动学习 **(**Motor Learning**)** ###

It is learning by precise movement of muscles. For example, picking objects, writing, etc.

它是通过精确的肌肉运动来学习的。 例如，拾取对象，书写等。

### 观察学习 **(**Observational Learning**)** ###

To learn by watching and imitating others. For example, child tries to learn by mimicking her parent.

通过观看和模仿他人来学习。 例如，孩子试图通过模仿父母来学习。

### 知觉学习 **(**Perceptual Learning**)** ###

It is learning to recognize stimuli that one has seen before. For example, identifying and classifying objects and situations.

它正在学习认识一个人以前见过的刺激。 例如，识别和分类对象和情况。

### 关系学习 **(**Relational Learning**)** ###

It involves learning to differentiate among various stimuli on the basis of relational properties, rather than absolute properties. For Example, Adding ‘little less’ salt at the time of cooking potatoes that came up salty last time, when cooked with adding say a tablespoon of salt.

它涉及学习根据关系属性而不是绝对属性来区分各种刺激。 例如，在烹饪上次咸的土豆时添加“少一点”的盐，当煮熟时添加一汤匙的盐。

*  **Spatial Learning** − It is learning through visual stimuli such as images, colors, maps, etc. For example, A person can create roadmap in mind before actually following the road.
    
    **空间学习** \-它是通过视觉刺激(例如图像，颜色，地图等)进行学习的。例如，一个人可以在实际走道路之前在脑海中创建路线图。
 *  **Stimulus-Response Learning** − It is learning to perform a particular behavior when a certain stimulus is present. For example, a dog raises its ear on hearing doorbell.
    
    **刺激React学习** \-它是在存在某种刺激时学习执行特定行为的方法。 例如，一条狗在听到门铃时举起耳朵。

### 解决问题 **(**Problem Solving**)** ###

It is the process in which one perceives and tries to arrive at a desired solution from a present situation by taking some path, which is blocked by known or unknown hurdles.

在这一过程中，人们通过采取某种途径来感知并尝试从当前状况中获得所需的解决方案，而这一过程被已知或未知的障碍所阻止。

Problem solving also includes **decision making**, which is the process of selecting the best suitable alternative out of multiple alternatives to reach the desired goal.

解决问题还包括**决策** ，这是从多个备选方案中选择最合适的备选方案以实现所需目标的过程。

### 知觉 **(**Perception**)** ###

It is the process of acquiring, interpreting, selecting, and organizing sensory information.

它是获取，解释，选择和组织感官信息的过程。

Perception presumes **sensing**. In humans, perception is aided by sensory organs. In the domain of AI, perception mechanism puts the data acquired by the sensors together in a meaningful manner.

知觉假定**感觉** 。 在人类中，感觉是由感觉器官协助的。 在AI领域，感知机制以有意义的方式将传感器获取的数据组合在一起。

### 语言智能 **(**Linguistic Intelligence**)** ###

It is one’s ability to use, comprehend, speak, and write the verbal and written language. It is important in interpersonal communication.

它是使用，理解，说和写口头和书面语言的能力。 这在人际交流中很重要。

## AI涉及什么 **(**What’s Involved in AI**)** ##

Artificial intelligence is a vast area of study. This field of study helps in finding solutions to real world problems.

人工智能是一个广阔的研究领域。 该研究领域有助于找到解决现实问题的方法。

Let us now see the different fields of study within AI −

现在让我们看看AI的不同研究领域-

### 机器学习 **(**Machine Learning**)** ###

It is one of the most popular fields of AI. The basic concept of this filed is to make the machine learning from data as the human beings can learn from his/her experience. It contains learning models on the basis of which the predictions can be made on unknown data.

它是AI最受欢迎的领域之一。 该字段的基本概念是使机器可以从数据中学习，就像人类可以从他/她的经验中学到的那样。 它包含学习模型，可以基于这些模型对未知数据进行预测。

### 逻辑 **(**Logic**)** ###

It is another important field of study in which mathematical logic is used to execute the computer programs. It contains rules and facts to perform pattern matching, semantic analysis, etc.

这是另一个重要的研究领域，其中使用数学逻辑来执行计算机程序。 它包含规则和事实以执行模式匹配，语义分析等。

### 正在搜寻 **(**Searching**)** ###

This field of study is basically used in games like chess, tic-tac-toe. Search algorithms give the optimal solution after searching the whole search space.

该研究领域基本上用于象棋，井字游戏中。 在搜索整个搜索空间后，搜索算法会提供最佳解决方案。

### 人工神经网络 **(**Artificial neural networks**)** ###

This is a network of efficient computing systems the central theme of which is borrowed from the analogy of biological neural networks. ANN can be used in robotics, speech recognition, speech processing, etc.

这是一个高效计算系统的网络，其中心主题是从生物神经网络的类比中借用的。 ANN可用于机器人技术，语音识别，语音处理等。

### 遗传算法 **(**Genetic Algorithm**)** ###

Genetic algorithms help in solving problems with the assistance of more than one program. The result would be based on selecting the fittest.

遗传算法借助多个程序帮助解决问题。 结果将基于选择最适合者。

### 知识表示 **(**Knowledge Representation**)** ###

It is the field of study with the help of which we can represent the facts in a way the machine that is understandable to the machine. The more efficiently knowledge is represented; the more system would be intelligent.

在这个研究领域中，我们可以用机器可以理解的方式表示事实。 代表知识的效率更高； 更多的系统将是智能的。

## AI的应用 **(**Application of AI**)** ##

In this section, we will see the different fields supported by AI −

在本节中，我们将看到AI支持的不同字段-

### 赌博 **(**Gaming**)** ###

AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.

人工智能在象棋，扑克，井字游戏等战略游戏中起着至关重要的作用，在这种游戏中，机器可以根据启发式知识来思考大量可能的位置。

### 自然语言处理 **(**Natural Language Processing**)** ###

It is possible to interact with the computer that understands natural language spoken by humans.

可以与理解人类所说自然语言的计算机进行交互。

### 专家系统 **(**Expert Systems**)** ###

There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users.

有些应用程序将机器，软件和特殊信息集成在一起，以进行推理和建议。 他们向用户提供解释和建议。

### 视觉系统 **(**Vision Systems**)** ###

These systems understand, interpret, and comprehend visual input on the computer. For example,

这些系统理解，解释和理解计算机上的视觉输入。 例如，

*  A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas.
    
    间谍飞机拍摄照片，用于找出空间信息或区域地图。
 *  Doctors use clinical expert system to diagnose the patient.
    
    医生使用临床专家系统来诊断患者。
 *  Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.
    
    警察使用计算机软件，该软件可以利用法医存储的肖像识别罪犯的脸。

### 语音识别 **(**Speech Recognition**)** ###

Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc.

一些智能系统能够在人们与之交谈的同时，根据句子及其含义来听和理解该语言。 它可以处理不同的口音，语，背景噪音，由于寒冷引起的人声变化等。

### 手写识别 **(**Handwriting Recognition**)** ###

The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text.

手写识别软件读取由笔在纸上或由手写笔在屏幕上书写的文本。 它可以识别字母的形状并将其转换为可编辑的文本。

### 智能机器人 **(**Intelligent Robots**)** ###

Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment.

机器人能够执行人类给出的任务。 它们具有传感器，可以检测来自现实世界的物理数据，例如光，热，温度，运动，声音，撞击和压力。 它们具有高效的处理器，多个传感器和巨大的内存，以展现智能。 此外，他们能够从错误中学习，并且能够适应新环境。

## 认知建模：模拟人类思维过程 **(**Cognitive Modeling: Simulating Human Thinking Procedure**)** ##

Cognitive modeling is basically the field of study within computer science that deals with the study and simulating the thinking process of human beings. The main task of AI is to make machine think like human. The most important feature of human thinking process is problem solving. That is why more or less cognitive modeling tries to understand how humans can solve the problems. After that this model can be used for various AI applications such as machine learning, robotics, natural language processing, etc. Following is the diagram of different thinking levels of human brain −

认知建模基本上是计算机科学中的研究领域，它涉及研究并模拟人类的思维过程。 AI的主要任务是使机器像人一样思考。 人类思维过程的最重要特征是解决问题。 这就是为什么或多或少的认知建模试图理解人类如何解决问题的原因。 之后，该模型可用于各种AI应用，例如机器学习，机器人技术，自然语言处理等。以下是人脑不同思维水平的图表-

![Cognitive Modeling][]

## 代理与环境 **(**Agent & Environment**)** ##

In this section, we will focus on the agent and environment and how these help in Artificial Intelligence.

在本节中，我们将重点介绍代理和环境以及这些对人工智能的帮助。

### 代理商 **(**Agent**)** ###

An agent is anything that can perceive its environment through sensors and acts upon that environment through effectors.

代理是可以通过传感器感知其环境并通过效应器在该环境上起作用的任何事物。

*  A **human agent** has sensory organs such as eyes, ears, nose, tongue and skin parallel to the sensors, and other organs such as hands, legs, mouth, for effectors.
    
    **人类试剂**具有与传感器平行的感觉器官，例如眼睛，耳朵，鼻子，舌头和皮肤，以及其他器官，例如效应器的手，腿，嘴。
 *  A **robotic agent** replaces cameras and infrared range finders for the sensors, and various motors and actuators for effectors.
    
    **机器人代理**代替了用于传感器的照相机和红外测距仪，以及用于效应器的各种电机和致动器。
 *  A **software agent** has encoded bit strings as its programs and actions.
    
    **软件代理**已将位字符串编码为其程序和动作。

### 环境 **(**Environment**)** ###

Some programs operate in an entirely **artificial environment** confined to keyboard input, database, computer file systems and character output on a screen.

一些程序在完全**人工的环境中**运行，仅限于键盘输入，数据库，计算机文件系统和屏幕上的字符输出。

In contrast, some software agents (software robots or softbots) exist in rich, unlimited softbots domains. The simulator has a **very detailed, complex environment**. The software agent needs to choose from a long array of actions in real time. A softbot is designed to scan the online preferences of the customer and shows interesting items to the customer works in the **real** as well as an **artificial** environment.

相反，某些软件代理(软件机器人或软件机器人)存在于丰富的，无限的软件机器人域中。 该模拟器具有**非常详细，复杂的环境** 。 软件代理需要实时从多种操作中进行选择。 软件机器人的设计目的是扫描客户的在线偏好，并在**真实**和**人工**环境中向客户展示有趣的项目。

> 翻译自: [https://www.tutorialspoint.com/artificial\_intelligence\_with\_python/artificial\_intelligence\_with\_python\_primer\_concepts.htm][https_www.tutorialspoint.com_artificial_intelligence_with_python_artificial_intelligence_with_python_primer_concepts.htm]

python入门概念

[python]: /images/20221123/5a8ec88f3369496884026a7389154245.png
[Intelligence]: /images/20221123/aac97d2e77464ae4bd87d3508ef748d1.png
[Cognitive Modeling]: /images/20221123/317dfe846a34459888c91a46c16c742d.png
[https_www.tutorialspoint.com_artificial_intelligence_with_python_artificial_intelligence_with_python_primer_concepts.htm]: https://www.tutorialspoint.com/artificial_intelligence_with_python/artificial_intelligence_with_python_primer_concepts.htm