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6 Reasons Why Python Can Ace AI and Machine Learning Applications?

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6 Reasons Why Python Can Ace AI and Machine Learning Applications?

The current age is the age of automation, personalization, smart devices, and digitization. If you use your phone daily, you must have seen countless ads. The cool thing about these ads is that they are curated based on your search preferences.


Some cool facts about Python!


  1. Some functions in Python can return multiple values as compared to Java and C.
  2. A Python file is stored as a .pyc file which acts as a dynamic engine eliminating the need for a compiler in Python.
  3. You can easily implement the “else” clause within the “for” loop in Python.
  4. Python has a variant in both C and Java.
  5. The Zen of Python is an immortal prayer written about Python.


Why is Python favored for AI and Machine Learning?


6 Reasons Why Python Can Ace AI and Machine Learning Applications, image #2


There is not one but many reasons for choosing Python for developing AI and Machine Learning solutions. Here are some of those reasons!


A plethora of libraries


AI development solutions and Machine Learning development solutions require complex data calculations. Therefore, Python provides you with libraries like Numpy, Pandas, and others for faster computations. Here are some of the libraries of Python:


  • Pandas: As mentioned, Pandas is a library that is used for high-level data computation and analysis. Big data analysis is powerfully backed by Pandas. You can collect, filter, merge and even import data from excel.


  • TensorFlow: Machine Learning also has a subset named deep learning. The technology is primarily used in AI applications and deals with utilizing artificial neural networks for big datasets.


  • Matplotlib: To make it easy for you to visualize data in various forms like charts, histograms, 2D plots, Python provides you with Matplotlib.


  • Keras: Keras has the capability to access both the CPU as well as GPU of your system. This allows it to make speedy calculations, thus making it ideal for deep learning.


  • Scikit-Image: This is an innovative Python library ideal for image processing.


  • Scikit Learn: Scikit learn is a Python library that is used to manage various Machine Learning algorithms such as classification, regressions, clustering, and many more.


  • PyBrain: It is a library that primarily uses neural networks and reinforcement learning.


These are just some of the Python libraries. There are many others that you can use to develop powerful apps and software. However, you may also have to hire python developer for the same.


Python is the most preferred language in the world today. But is it good for AI and ML? Check out this article to know!

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