In this blog, we’ll discuss the ‘why’ behind Python’s popularity in the world of AI and machine learning or in a simple sense the role of Python for ML & AI
Have you wondered?? how video-streaming services such as YouTube and Netflix fetch videos that you like? Or how do Google and Facebook find stories that are interesting to you?
So, this is because of Artificial Intelligence (AI) and Machine Learning (ML) algorithms – These algorithms are coded using a programming language in such a way that they can analyze your behavior.
AI & ML: Quick Recap
1.) Artificial Intelligence
AI is the ability of a machine to display human-like capabilities such as reasoning, learning, planning, and creativity.
Example of Artificial Intelligence (AI):
- Self Driving Cars: Artificial Intelligence (AI) can be used to create a fully autonomous car to travel.
- Sign and Voice Recognizer (SVR): It recognizes sign language gestures of the wearer and converts them to speech.
- Sophia: Sophia is a social humanoid robot.
- Face recognition systems
- Drones and more…
2.) Machine Learning
Machine learning is the study of using algorithms and data that allow computers to perform tasks without instructions or input from human users. It is a subset of Artificial Intelligence (AI), Machine learning structures in data to enable learning, reasoning, and decision making outside of human interaction.
Example of Machine Learning (ML):
- Snapchat Filters: Snapchats filters use augmented reality and machine learning for your flower crowns selfies.
- Netflix: The Netflix recommendation system is powered by Machine Learning (ML) algorithms and that is what makes their system so good in predicting the movies that you are most likely to watch.
>> Machine Learning Categories
1. Supervised learning: The machine learns from labeled data. Normally, the data is labeled by humans. It can be separated into two types of problems when data mining—classification and regression.
2. Unsupervised learning: The machine learns from un-labeled data. It includes clustering, anomaly detection, neural networks, etc.
3. Reinforcement learning: The machine learns through a reward-based system. It is about taking suitable action to maximize reward in a particular situation.
Also Check: Our blog post on Python Pandas.
Python Overview
Python is a versatile coding language that can be used for back-end development, software development, and data science among other areas. Because this programming language is accessible, portable, and can be run on Mac, Windows, or Unix. The Python programming language best fits Machine learning and AI due to its independent platform and its popularity in the programming community.
Applications of Python
Python is used in various software domains some application areas are given below:
- Web and Internet Development
- Games
- Scientific and computational applications
- Image processing and graphic design applications
- Enterprise and business applications development
- GUI based desktop applications
Reasons To Choose Python For ML & AI
With each passing minute, AI and machine learning are grabbing more eyeballs than ever. Who would have thought that there could exist a self-driven car or smartphone that forecasts what weather it will be tomorrow! But today, all this is a reality.
Companies like Uber, Tesla, JP Morgan Chase, Apple, and other industry giants have accepted these technologies. With this, they’ve also befriended one programming language that is flexible, stable, with a variety of tools available: PYTHON.
When you code with Python programming language, you get a well-structured & tested environment where you can quickly turn your ideas into action. Also, it takes less coding and time to solve problems. Python offers some great reasons to pick it as the programming language Python for ML & AI.
Why Python for ML (Machine Learning) & AI (Artificial Intelligence)?
1. Simple and Consistent
Python offers concise, readable codes. As complex algorithms stand behind AI and ML, the simplicity of the language helps in developing reliable systems.
Another reason which makes Python so popular is that it is an easy-to-learn programming language. It is suitable for a collaborative implementation as and when multiple developers are involved. And being a general-purpose language, it allows users to build prototypes faster so that they can test their product for machine learning.
2. Rich Library Ecosystem
Implementing AI and ML algorithms can be tricky and require a lot of time. It’s vital to have a well-structured and well-tested environment to enable developers to come up with the best coding solutions. Python contains libraries that help in saving developer’s time as they do not have to start from scratch.
List of some common libraries used for AI and machine learning:
- Pandas
- Scikit-learn
- Keras
- TensorFlow
- Caffe
- PyBrain
With the help of these libraries, AI and ML algorithms can be implemented more easily. These libraries are useful for data analysis, deep learning, machine learning, computer vision, and advanced computing. This helps in the faster development of the product as the developers can now resolve complex problems without rewriting code lines.
3. Open-Source Nature
Python is an open-source language supported and administered by the Python Software Foundation. Thus, it is free to use, change, and distribute. Even more, the Python developers community is also open to everyone; therefore, encouraging, contributing, and growing Python open-source database.
4. Platform Independent
The platform independence of a programming language implies that it can run on a variety of platforms and software architectures. The code has to be written once and it can be compiled and run on multiple platforms.
Python is easy to learn and use and scores high on versatility. It can run on any platform, be it Windows, macOS, Linux, Unix, and more
5. Flexibility
Python is a great choice for AI and ML as it is very flexible:
- Developers can utilize different algorithms and languages along with Python a majority of code can be checked in the IDE.
- It works as an ideal backend and is suitable for linking different data structures together.
- It provides the option to choose between OOPs and scripting.
6. Great community support and popularity
Python is free, comes with useful libraries and tools, and its documentation can be accessed online. It is loved by millions of developers worldwide. Programmers can discuss their problem statements on forums and have conversations with others to find solutions.
7. Readability
One of the things that have made Python successful is its readability. Code is clear and easy to understand, includes good descriptive variable and function names, follows solid principles, and keeps functions short.
8. Visualization Options
As mentioned earlier also that Python comes with many libraries, some of which are great visualization tools. However, AI developers need to point out that it is vital to represent data in a human-readable format in AI, deep learning, and machine learning.
Libraries such as Matplotlib enable data scientists to create histograms, graphs, and plots to improve understanding, display, and data visualization. Different application programming interfaces simplify the visualization process and help make clear reports.
9. Growing Popularity
Python is becoming the most common programming language in the world. It is the choice of many well-known brands (such as Google, Amazon, Quora, Facebook, and Netflix) because of its simplicity, versatility, and ease of maintenance. They are usually used for some of the most exciting and innovative technologies, such as artificial intelligence, machine learning, and robotics.
Python Career Opportunities
There is a lot of Career Opportunities in Python, Some of them are->
- Python Developer
- Data Scientists
- Data Analyst
- Machine Learning Engineers
Which Companies are Using AI and ML?
Some of the top brands that utilize Python for AI and ML:
- Microsoft
- NASA
- JP Morgan Chase and more,
Conclusion
Python has created an emphatic place for itself as the industry has focussed on building for the future where data plays a central role, and Python, with its dexterity, has become the #1 language of choice for all AI and ML professionals.
Related References
- Deep Learning Vs Machine Learning
- Data Scientists vs Data Engineers vs Data Analyst
- An Introduction To Python For Microsoft Azure Data Scientist | DP-100
- Introduction to Python, Objects and Data Structure Basics Q&A
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