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Python for AI and What Else?

Let’s walk through a few popular use cases for Python programming, including web development, machine learning, scientific computing, function decorators, browser automation, and robotics.

Python has taken over the development space and Python is definitely for AI as well as many other application arenas. In fact, it's everywhere. Ask any coder, and they'll tell you that it's easy to learn and it's often the right tool for the job.

The programming language is also quite popular among data scientists and startups. That can give you an idea of how prevalent it will be in the near future. Python is number 3 in the most recommended languages to learn.

Further, installation programs like Anaconda and MATLAB can do amazing things with various operating systems (OS). Finally, Python has the added benefit of being a clean and straightforward syntax with a massive community-run library (NumPy, Pandas, SciPy, etc.).

This means that beginners and seasoned veterans will have access to millions of lines of code that can be easily borrowed from the best programmers (in the world) and used by anyone.

So what are some of the amazing things you can do with Python?

1. AI and Machine Learning (ML) Python

Finding fingerprint identifications, predicting stocks, and spam detection can all be achieved with ML. Coders can set this up by taking advantage of Python modules like scikit-learn,  Tensorflow, and Theano to support it. Besides, Python is great for any AI projects, especially ML, neural networks and generative AI.

For example, you can create a simple chatbot to ease out communication with your users. It doesn’t take much time and it is quite easy to do.

Here are a few more AI/ML use cases using Python:

  • Anomaly detection within a process, system, factory line, conversation, etc.
  • Personalized recommendation engine based on search, previous purchases and site navigation
  • Sentient chatbot that speaks your language
  • Process automation including workflows, onboarding, invoicing, contracts, compliance
  • Personal assistant who does scheduling, reminders, reservations, confirmations
  • Data insights and decision support thru conversational queries

2. Python Code for Web Development

As Python is an Object Oriented (OO) language, anyone starting will find it easy to play along with OO concepts. More seasoned coders can use it for Machine Learning (ML) algorithms and analysis as well as Big Data research and analytics.

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When it comes to web development, it’s a great option because you have a ton of choices like Django and Pyramid to work with. So you can build a cool website from scratch without feeling overwhelmed. You can also take advantage of micro-frameworks like Flask and Bottle.

Advanced content management is also possible with systems like Django CMS, Wagtail, and Plone. Further, Python’s standard library and web frameworks support several internet protocols like HTML, XML, and JSON.

Here are 10 top websites and social platforms built with Python:

  • reddit
  • Netflix
  • DropBox
  • Spotify
  • Uber
  • Lyft
  • Instagram
  • Pinterest
  • Survey Monkey
  • Quora

3. Scientific and Numeric Computing

Data analytics basically falls under scientific and numeric computing. To build something in this niche, you can take advantage of SciPy for mathematics, engineering, and science. Pandas is also a data analysis and modeling library, so there’s a lot going on with Python within data science.

If you need to edit and recode a work session, you can use IPython which is a powerful interactive shell. It also supports parallel computing and visualization.

Try NumPy to wrap data collections and manipulate them. For example, you can merge two data sets or create a histogram. Data scientists will also take advantage of the excellent Numpy array plotting capabilities.

If you want to make a progress report on the progress made in your field, you will enjoy using Jupyter Notebooks. It is primarily used for educating and explaining projects.

4. Function Decorators for Enhanced Functionality

Function decorators are neat in Python, as they allow developers to enhance the functionality of existing functions. So this can be translated into both web development and data analytics.

You can use decorators on functions like login into your site. Login/logout functions are a classic decorator example. They manage the actual functioning of a program.

For example, a decorator can add a date filter to your table. You want to display data from the last week instead of the previous month.

Another example is to password-protect a web page. All you need to do is make a function like the login_required function from IPython that checks the password. Then you can add it as a decorator on your page.

5. Browser Web Application Automation

You can also use Python to do incredible things, like automating your browser to do social media posts. This can be done by using Selenium with Python source code. The bot will run on your computer and take control of your browser. It can also perform tasks like sharing content on your social media pages.

You can use Selenium, Tricentis Tosca, and TestComplete to automate general web browsing, not just social media. So you can build something like a search engine bot, an online store bot, or an SEO link-checking bot.

Here are five more fabulous projects to develop with Python:

  • Webform automation to fill out the form and send it to the server.
  • Bidding bot to buy a product online by placing bids in an automated fashion.
  • Twitter bot that can post tweets and interact with users in a 2-way conversation.
  • Script to scrape web pages for data and place it in a database.
  • Browser-based bot to detect click fraud related to online ads and ensure it is not happening on your website.

6. Python Makes Robotics Possible

Python is an excellent foundation for coding a Raspberry Pi to function as the brain of a robot. By doing this, you get the robot to react to its environment and perform multiple actions.

For example, try a robot like TurtleBot by combining Raspberry Pi with a robot kit. Cameras, sensors, wheels, and a battery can be added to TurtleBot to make it mobile. You can also use external wireless devices like a Bluetooth controller, Wi-Fi adapter, or GPS module to move the robot autonomously. With Python programming, you can make the robot follow lines, avoid obstacles and move toward the light.

A robot like TurtleBot and iRobot can be programmed to make a search and rescue robot, a mobile robot, or even a moving security camera. There are many things you can do with this bot while using Python.

Wrapping Up

These six cool things made possible by this programming language is just a fraction of what you can do with it. Python’s latest release has new features in the asyncio module (which is no longer provisional with a surprisingly stable API), formatted string literals, and the addition of a file system path protocol.

Further, Python libraries which are the new JIT compiler helps to accelerate CPython by boosting its stock interpreter. This is achieved with a JIT API from CoreCLR project (Microsoft).

The language is also evolving fast within the data science space. The Python ecosystem is now full of data science tools, so a lot of the data science work that’s currently taking place is being done with open-source tools like Python.

Because it’s easy to learn, there’s also a growing segment of non-programmers learning and using Python’s data science tools. This changes the whole dynamic of the average Python user.

If you need assistance with building any type of software, hiring technically solid talent or want to learn more about how AI can transform your business, reach out to Intersog today.

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