What can python be used for?

What can python be used for? Let me introduce to you the application direction of Python:

01 Web development

Web frameworks based on Python such as Django and Flask have recently been used in Web development Very popular in.

These web frameworks can help you write server-side code (back-end code) in Python. This is the code that runs on your server, not the code that runs on the user's device and browser (front-end code).

02 Data Science

Data science, including machine learning, data analysis and data visualization.

1. What is machine learning

Suppose you want to develop a program that can automatically detect the content of images. Given Figure 1, you want the program to recognize that it is a dog.

Given Figure 2, I hope the program can recognize that this is a table.

You might say, I can write some code to do this. For example, if there are a lot of light brown pixels in the picture, it can be identified as a dog.

Or you can detect the edges in the picture. If there are many straight edges, then it is a table.

But this method soon becomes ineffective. What if the dog in the picture doesn’t have brown fur? What if the picture only shows the circular part of the table?

Machine learning is needed here.

Related recommendations: "Python Video Tutorial"

Machine learning implements algorithms that can automatically detect patterns in input.

For example, you input 1,000 pictures of dogs and 1,000 pictures of tables into a machine learning algorithm and let it learn the difference between dogs and tables. Then when you give it a new picture and ask it to identify whether it is a dog or a table, it will be able to make a judgment.

This is somewhat similar to the way children learn new things. How do children learn to recognize dogs or tables? Just through a lot of examples.

You wouldn’t explicitly tell your child, “If something furry has light brown hair, it’s probably a dog.”

You’d say, “This is a dog, and this is Dog. And this is a table, and that is a table."

Machine learning algorithms work in much the same way.

We can apply the same idea to:

Recommendation systems: such as YouTube, Amazon and Netflix

Face recognition

Voice recognition

and other applications.

The popular machine learning algorithms you have heard of include:

Neural Network

Deep Learning

Support Vector Machine

Random Forest

You can use any of the above algorithms to solve the image labeling problem mentioned earlier.

2. Using Python for machine learning

There are some popular machine learning libraries and Python frameworks. Two of the most popular are scikit-learn and TensorFlow.

scikit-learn comes with some popular machine learning algorithms built-in.

TensorFlow is a low-level library that allows you to create custom machine learning algorithms.

If you are just starting a machine learning project, it is recommended that you start with scikit-learn. If you start to have efficiency issues, then use TensorFlow.

3. Data Analysis and Data Visualization

Suppose you work for a company that sells products online. As a data analyst, you would draw a bar chart like this.

You can see from this picture that on a certain Sunday, male users purchased more than 400 products and female users purchased 350 products.

As a data analyst, you will come up with some possible explanations for this. The obvious explanation is that the product is more popular among male users. The other is that the sample size is too small and the difference is due to chance. It's also possible that for some reason, men tend to buy the product on Sundays.

To understand which interpretation is correct, you can draw another diagram.

03 Script

What is a script?

Scripting usually refers to writing small programs that can automatically perform simple tasks.

For example, the company has an email support system to respond to questions sent to us by customers via email.

If you want to count the number of emails containing keywords in order to analyze the emails we receive. This can be done manually, but you can automate this task by writing a simple script.

Ruby is a good choice for this type of task. Python is suitable for this type of task because it has a simple syntax, is easy to write, and is fast to test.

04 Other uses

1. Embedded applications

I am not an expert in this area, but I know that Python can be used with Rasberry Pi, Popular among hardware enthusiasts.

2. Game Development

You can use PyGame to develop games, but it is not the most popular game engine. You can use it to develop hobby projects, but if you are serious about game development, it is not recommended.

I recommend using Unity’s C#, which is one of the most popular game engines. It lets you develop games for many platforms, including Mac, Windows, iOS, and Android.

3. Desktop application

You can use Python’s Tkinter, but this is not the most popular choice. Languages ​​like Java, C# and C seem to be more popular.

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