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How to implement artificial intelligence in python

1. Python is an interpreted language. It is very convenient to write programs. The convenience of writing programs is very important for people who do machine learning. PYTHON library "IMITATION" .

Because it is often necessary to make various modifications to the model, which may affect the whole body in a compiled language, it can usually be implemented in Python in very little time.

For example, when writing a matrix multiplication in a compiled language such as C, you need to allocate memory for the operands (matrix), allocate memory for the result, manually call gemm on the BLAS interface, and finally, if the smart pointer is not used, you have to manually reclaim the memory space. .

Python is almost a matter of import numpy; in two sentences. Of course, many C/C++ libraries now support managed memory management, which makes the development process much easier, but interpreted languages still have a natural advantage - no compilation time is required.

This is very beneficial to work efficiency for research directions such as machine learning that require a lot of prototyping and iteration.

2. Python’s development ecosystem is mature. There are many useful libraries that can be used with Python’s flexible syntax. It also makes very practical functions including text operations, list/dict comprehension, etc. very easy to implement efficiently (both writing and running efficiency are high), and it can be used with lambda, etc. It is even more convenient to use.

This is also a major reason behind Python’s benign ecology.

In comparison, although Lua is also an interpreted language and even has the blessing of artifacts like LuaJIT, it is difficult for it to achieve the same level as Python. One is because Python is the predecessor that occupies the market share, and the other is because of its various counter-intuitive features. design (such as global variables).

However, with the help of Lua-Python bridge and Torch, Lua seems to be parasitic on the rise. 3. The development of Python’s ultra-high efficiency interpreted language has far exceeded many people’s imagination.

Many syntactic sugars such as list comprehension are implemented close to the kernel. In addition to JIT, there is also Cython that can greatly increase operating efficiency.

Finally, thanks to Python's C interface, many efficient and Python interface-friendly libraries like gnumpy and theano can speed up the running of programs. With the support of a strong team, these libraries may be more efficient than an unskilled programmer. The efficiency of C writing and tuning in one month is even higher.

The development prospects of the Python language in the next ten years are very good. There is no doubt that more and more companies will use the Python language, and the talent gap for Python programmers will also become larger and larger. Look for the opportunity, seize the opportunity, Python full stack Popular positions such as development engineer, Python development engineer, automation development engineer, Linux operation and maintenance engineer, Python crawler development engineer, front-end development engineer, big data analysis and data mining are waiting for you to choose.

Google Artificial Intelligence Writing Project: Xiaofamao

Python is a very popular language in recent years. Let’s talk about the relationship between python and artificial intelligence.

In what fields can python be applied?

① Web development: Many large websites are developed in Python.

Douban: Almost all of the company's business is developed through python Zhihu: The largest question and answer community in China, developed through python (Quora) Dr. Chunyu: Well-known domestic online medical websites are developed using python, including Sohu, Kingsoft, Tencent, Shanda, NetEase, Baidu, Alibaba, Taobao, Tudou, Sina, Guoke and other companies are using python to complete various tasks.

Foreign websites: Google: Google App Engine, Google Earth, Google Crawler, Google Ads and other projects are using Python extensively to develop CIA: The CIA website is developed using Python NASA: The National Aeronautics and Space Administration (NASA) uses Python extensively for data processing Analysis and calculation YouTube: The world's largest video website YouTube is developed by python Dropbox: The largest online cloud storage website in the United States, all implemented in python, the website handles the upload and download of 1 billion files every day Instagram: The largest picture sharing social network in the United States Website, more than 30 million photos are shared every day, all developed in python. Facebook: A large number of basic libraries are implemented through python. Redhat: The yum package management tool in the new version of the most popular Linux in the world is developed in python② Crawlers: Now is the era of big data. Crawlers are a common scenario in operations. For example, Google’s crawlers were written in Python in the early days. If you are interested in collecting and processing data, a crawler engineer will be a great candidate. Good choice.

③ Data analysis: Generally, after we use a crawler to crawl a large amount of data, we need to process the data for analysis, otherwise the crawler will crawl in vain. Our ultimate goal is to analyze the data. In this regard, there are also very rich libraries for data analysis. , various graphical analysis diagrams, etc. can be made.

It is also very convenient. Visualization libraries such as Seaborn can plot data using only one or two lines, while using Pandas, Numpy, and scipy can simply perform calculations such as screening and regression on large amounts of data.

④ Artificial intelligence: The main reason why Python has become well-known in recent years is the rise of the field of artificial intelligence. Python has always had a good reputation in the field of scientific computing. Its concise and clear syntax and rich computing tools are deeply loved by developers in this field.

Python has the characteristics of simple writing and few changes. Especially suitable for use in the direction of machine learning. And provides a rich library. Reduces the cost of learning artificial intelligence.

Is there a small example of Python artificial intelligence on the official website of Silicon Valley? , describe python artificial intelligence

How to make a small artificial intelligence with Python

Why python is the first choice for artificial intelligence

1. Life is short, I use Python: simple, efficient, and easy to get started. Before discussing why we choose Python, we must first know what Python is. Python is an object-oriented, interpreted computer programming language.

It is designed to be elegant, clear and simple. Compared with the Java language, which is also object-oriented, functions, modules, strings, and numbers are all objects for Python, unlike Java where there are basic types.

Some friends may ask, as a scripting language, Python is not as fast as Java and C++, so why should you choose Python? The core calculations of artificial intelligence are all written in C language, and Python only writes logic.

It’s not that C language can’t write upper-level logic, it’s just that the amount of code is too large and development efficiency is low. The running speed can be improved through hardware upgrades, but the development speed cannot be improved by stacking manpower. For current AI applications, rapid development is more effective than rapid execution.

2. Python has a rich and powerful library, nicknamed the glue language. As we mentioned above, the real calculation of artificial intelligence relies on the C language. If you want to write the logic of artificial intelligence, you need an excuse to switch from other languages to C language. Python is the lowest and easiest one.

Moreover, Python has historically served as an important tool for scientific computing and data analysis. Basic libraries such as numpy not only reduce the development workload, but also make it easier for practitioners to get started.

3. Python has a wide range of application fields. It supports the development of aerospace and aviation systems, and can do almost everything from the development of small games. Python is a general-purpose language and can be used anywhere, but the best application scenarios are those that pursue development speed and do not care much about operating efficiency.

The biggest application of Python now is the web backend, and then there are Linux system management, rapid prototype development under various platforms, gadget writing, or as a glue language to schedule things written in other languages. Here we give a few simple examples.

①Web application development server-side programming, with rich web development frameworks, such as Django and TurboGears, to quickly complete the development of a website and web services. Typical examples include domestic Douban, Guoke.com, etc.; foreign Google, Dropbox, etc.

② System network operation and maintenance In the operation and maintenance work, there is a lot of repetitive work, and management systems, monitoring systems, release systems, etc. need to be built to automate the work and improve work efficiency. In such a scenario, Python is a very Appropriate language.

③3D game development Python has a good 3D rendering library and game development framework. There are many games developed using Python, such as Disney Toon City and Blade of Darkness.

PyGame, Pykyra, etc. are commonly used. Python is also a good choice for students who want to enter the game industry.

4. In the 2018 IEEE Spectrum programming language rankings, Python completely ditched Java and ranked first among 48 programming languages. Python not only ranked first, but also ranked first in the comprehensive index, user growth rate, employment advantage and open source language.

People who develop artificial intelligence are not necessarily very professional programmers. Many people in academia and data analysis are not familiar with programming. If you want to choose a language to get started with programming, Python is definitely the first choice.

It has streamlined many unnecessary symbols to facilitate reading and understanding, and is as close to natural language as possible. Programming is simple and direct, and is suitable for beginner programmers. Even a novice who is not a computer major can get started in minutes. This is why Python can be chosen and loved by so many people.

5. Python is the first introductory programming language for education in large, medium and small schools. It can be said to be a direct connection to artificial intelligence and an introduction to middle and high school programming. As a programming language, Python’s popularity and influence have continued to rise this year, and it has risen to the level of national strategy. superior.

Shandong Province has added Python content to its latest sixth-grade primary school information technology textbook; there have been rumors in the programming community that Zhejiang Province will make changes to middle school information technology textbooks. VB is dead and Python is here to stay.

The relevant national education departments attach great importance to the "popularization of artificial intelligence". They not only include Python in the traditional education system such as primary school, middle school and high school, but also lay the foundation for artificial intelligence talent training for the future development of the country and society. The bottom level promotes "all people learn Python" to the top level, thereby further realizing the promotion of artificial intelligence technology and the change of social talent structure.

What do you use Python for?

Once I knew I could do this, I really wanted to do it. Because of paper review and answer confirmation query; I want to know about Douban movies with a score of 8 or above, or time-travel movies, processing salary data assessment forms, etc.

What can be done 1. The main function of the answer artifact of "Shanghaiba" is to obtain unlimited answers to the questions on the "Shanghaiba" website (bypassing IP restrictions), and it also realizes the automatic recognition of verification codes. You only need to enter the URL of a certain question to get it with one click. Get answers, fast.

"If you want haha, is it necessary to help yourself or your children with homework?

” 2. Capture all students’ names, student numbers and course selection information in a certain system 3. Scan users with weak passwords on the graduate student system, simulate login to the library system and automatically renew loans 4. Submit spam messages to phishing websites in batches and often receive messages containing SMS linked to phishing websites are generally used to steal QQ passwords. In fact, you can use Python to submit junk data to the other party's server in batches (packets need to be captured first), so that scammers will not know which ones are genuine after seeing the information. Which ones are fake? Maybe we can save some students who filled in their passwords.

5. NetEase Cloud Music Batch Download allows you to batch download songs from NetEase Cloud Music Hot Song List. You can set the quantity yourself and the speed is very fast.

6. Batch download all articles of a certain issue of Reader Magazine 7. Obtain city PM2.5 concentration and ranking 8. Crawl commodity price information from a certain website. What do you use Python for?

As a powerful programming language, Python is favored by many developers because it is easy to learn. So, what are the application areas of Python?

Python has a wide range of application fields. Almost all large and medium-sized Internet companies are using Python to complete various tasks, such as Google, Youtube, Dropbox in foreign countries, Baidu, Sina, Sohu, Tencent, Alibaba, NetEase, Taobao, etc. in China. Zhihu, Douban, Autohome, Meituan, etc.

To sum up, the main application areas of Python are as follows. Web application development Python is often used for Web development. Although PHP and JS are still the mainstream languages for Web development, Python is gaining momentum.

Especially as Python's web development framework gradually matures (such as Django, flask, TurboGears, web2py, etc.), programmers can more easily develop and manage complex web programs.

For example, through the mod_wsgi module, Apache can run Web programs written in Python.

Python defines the WSGI standard application interface to coordinate communication between HTTP servers and Python-based Web programs.

To give the most intuitive example, Google, the world's largest search engine, extensively uses the Python language in its online search system.

In addition, Douban (shown in Figure 1), which we often visit and integrates movies, reading, and music, is also implemented using Python.

Figure 1 Douban implemented in Python Not only that, the world's largest video website Youtube and Dropbox (a network file synchronization tool) are also developed using Python.

Automated operation and maintenance In many operating systems, Python is a standard system component. Most Linux distributions as well as NetBSD, OpenBSD and Mac OS X have integrated Python, and Python can be run directly under the terminal.

There are some Linux distribution installers written in Python language, such as Ubuntu's Ubiquity installer, Red Hat Linux and Fedora's Anaconda installer, and so on.

In addition, the Python standard library contains multiple libraries that can be used to call operating system functions.

For example, through the pywin32 package, we can access Windows COM services and other Windows APIs; using IronPython, we can directly call the .Net Framework.

Usually, system management scripts written in Python are better than ordinary shell scripts in terms of readability, performance, code reuse, and scalability.

Artificial Intelligence is a very popular research direction in the field of artificial intelligence. If you want to select the hottest and highest-paying IT jobs, then engineers in the field of artificial intelligence have the most say.

Python is a mainstream programming language in machine learning, neural networks, deep learning, etc. in the field of artificial intelligence.

It can be said that artificial intelligence developed based on big data analysis and deep learning is essentially inseparable from the support of Python. There are at least the following reasons: Currently, the world’s excellent artificial intelligence learning frameworks, such as Google’s TransorFlow (Neural Network Framework), FaceBook's PyTorch (Neural Network Framework), and the Karas Neural Network Library of the open source community, etc., are all implemented in Python; Microsoft's CNTK (Cognitive Toolkit) also fully supports Python, and the company developed VS Code has also supported Python as a first-level language.

Python is good at scientific calculations and data analysis, supports various mathematical operations, and can draw higher-quality 2D and 3D images.

In short, the advent of the AI era has made Python stand out from many programming languages. Python's position as the leading language in the AI era is basically unshakable!

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You can go and add it and take a look ~ Web crawler Python language has been used to write web crawlers for a long time. Search engine companies such as Google heavily use Python language to write web crawlers.

From a technical level, Python provides many tools for writing web crawlers, such as urllib, Selenium and BeautifulSoup, etc. It also provides a web crawler framework Scrapy.

Scientific Computing Since 1997, NASA has used Python extensively to perform various complex scientific operations.

Moreover, compared with other interpreted languages (such as shell, js, PHP), Python has quite complete and excellent libraries in data analysis and visualization, such as NumPy, SciPy, Matplotlib, pandas, etc., which can satisfy Python programmers when writing Scientific computing program.

Game development Many games use C++ to write high-performance modules such as graphics display, and use Python or Lua to write game logic.

Compared with Python, Lua has simpler functions and smaller size; while Python supports more features and data types.

For example, the internationally designated game Sid Meier's Civilization (shown in Figure 2) is implemented using Python.

Figure 2 Games developed in Python In addition, Python can directly call Open GL to implement 3D rendering, which is the technical basis for high-performance game engines.

In fact, there are many game engines implemented in Python language, such as Pygame, Pyglet and Cocos 2d.

The above is only an introduction to the "tip of the iceberg" in Python application fields. For example, you can also use Pygame for game programming; use PIL and other tools for image processing; use the PyRo toolkit for robot control programming, etc.

Interested readers can search for information on their own to learn more.

What are the application fields of python?

For students who want to learn Python, the most important thing to know is its application fields. Only after understanding it can you clarify your goals. Let’s take a look at the application fields of Python: 1. Cloud computing PYTHON language It is the most popular language in cloud computing, and OpenStack is a typical application.

2. Web front-end development Compared with PHP and Ruby, the modular design of Python is very conducive to function expansion. Over the years, a large number of excellent web development frameworks have been formed and are constantly iterating.

Currently, excellent full-stack frameworks include Django and Flask, both of which inherit the simple and clear style of Python. They have high development efficiency, are easy to maintain, and are well integrated with automated operation and maintenance.

3. Artificial intelligence applications developed based on big data analysis and deep learning are essentially inseparable from the support of python. Currently, the world's outstanding artificial intelligence learning frameworks such as Google's TransorFlow, FaceBook's PyTorch and the neural network library of the open source community Karas and others are implemented in python.

Even Microsoft's CNTK (Cognitive Toolkit) fully supports Python, and Microsoft's Vscode already supports Python as a first-level language.

4. System operation and maintenance engineering project Python is very closely integrated with the operating system and managed. Currently, all Linux distributions include Python, and there are a large number of modules available for related management functions in Linux, such as the current mainstream Automated configuration management tool: SaltStackAnsible (currently RedHat).

At present, in almost all Internet companies, the standard configuration for automated operation and maintenance is python+Django/flask. In addition, openstack, which has become the de facto standard in virtualization management, is implemented in Python, so Python is a necessary skill for all operation and maintenance personnel.

5. Financial management analysis, quantitative trading, financial analysis, in the field of financial engineering, Python language is not only in use, but also the most used, and its importance is increasing year by year.

Reason: As a dynamic language, Python has a clear and simple language structure, rich libraries, mature and stable, and is very powerful in scientific calculation and statistical analysis. Its production efficiency is much higher than that of c, c++, and java. It is especially good at strategy backtesting.

How to implement artificial intelligence in python

The process of program learning is the process of using gradient descent to change the parameters of the algorithm model. For example, f(x) = aX+b; the parameters here are a and b. Use data to train the algorithm model to change the parameters, so that the algorithm model can realize face recognition and speech recognition.

The foundation for realizing artificial intelligence is algorithms, and python is a language for implementing algorithms. Because of the ease of use and data processing friendliness of python language, many people now use python language to do machine learning.

Other languages such as java, c++, etc. can also implement artificial intelligence related algorithms. The figure below is a schematic diagram of a neural network.