Why Python is best choice for developing Artificial Intelligence, Machine Learning and Deep Learning Solutions

, Why Python is best choice for developing Artificial Intelligence, Machine Learning and Deep Learning Solutions

Python is the most appreciated high level programming language among developers across the globe – from complex application development, process automation, scalable backend development to AI & ML solutions; it’s used everywhere. 

Perhaps, you must have known about AI and ML.  Artificial Intelligence is a machine demonstrated intelligence developed to achieve efficient solutions without direct intervention of the humans. Machine Learning is the data driven computer algorithms that helps in informed decision making. 

In order to improve the overall operational efficiency, companies are investing heavily in the machine learning products and resources. 

All the well-known products and consumer facing businesses are effectively utilizing data with the help of advanced learning algorithms to improve the customer experience and get a hawk eye view of what they are doing and what they should do. 

Professionals are selecting python over other languages. Let’s see what makes Python good fit for projects involving AI and ML. 

1. Easy to use open source language

Ease of using the python in the development of custom algorithms is the most important reason why Python is popular among developers. Its easily readable syntax makes it understandable and developers love this as they get to spend time on actual development rather than learning the technicalities involved in the language. 

2. Extraordinary Library Ecosystem

A library is basically a module or group of modules which consists of ready-made code bits that allows developers with certain functionalities or to perform actions. Development of AI and ML algorithms takes time and python library and framework ecosystem facilitates the development of these custom algorithms without having to develop them from scratch and with advantage saving crucial development time. As developers require well-structured and well-tested development environment which can help them provide the best solutions, python is their first choice. 

Python has  an extensive set of libraries and frameworks to ease the development of machine learning, artificial intelligence and deep learning solutions, some of the notable libraries that are used are:

  • Pandas – High level data structures and analysis tool that is handy for data analysis and manipulation by putting into tabular form. 
  • TensorFlow – It is very important and critical library that is pivotal in developing deep learning models. It is used to expedite computation and large scale machine learning algorithms. 
  • Keras – It’s an effective, user friendly, extensible open source library that used for developing and evaluating deep learning models. 
  • Scikit-learn – Used for clustering, regressions, classification and also supports a number of numerical and scientific libraries. 
  • Matplotlib – It is a plotting library that is used for visualization like creating 2D plots, charts, histograms etc. 
  • NLTK – It is one of the leading platform to work with human language data, natural language understanding (NLU) and natural language processing (NLP) and is applicable to chatbots. 
  • Caffe – A deep learning framework that is used for image classification and helps image processing at large scale.

3. Community and corporate support

Python has been around for a very long time and has developed an active community and helps developers to learn and hone up their python knowledge. There are many resources available from ML tutorials and YouTube videos that are a huge help for python developers and students as well. 

Besides, there is a lot of corporate support for Python for its ML abilities. Many top companies use python use python for their own products, and companies like Google have developed libraries for machine learning.

4. Flexibility

Flexibility is another core advantage of using Python for your AI and ML development projects. It allows developers to tackle the situation comfortably by providing various options and reducing the possibility of errors. 

  • Developers can combine Python with other programming languages and can easily link different data structures to work as ideal backend. 
  • It does not require recompiling source code, facilitating easy changes in the coding and ability to review results quickly. 

In addition to these benefits, python allows developers to select the development styles based on their requirements. Some of them are

  • Functional Style 
  • Imperative Style 
  • Object Oriented Style
  • Procedural Style

5. Visualization Support

Python has an extensive set of libraries and some of them do wonders for visualization requirements. In case of AI, ML or Deep Learning solutions, presenting the datasets in the easily readable format  are very important and there is no other way that presenting it in a visual format. 

Python libraries help them to build charts, histograms and other visual presentations which expedite the visualization and helps make the clear reports and integrated visual dashboards. 

6. Platform Independence

Python for AI-ML development can run on any platform, be it Windows, Mac-OS or Linux and 20 plus other platforms. 

With some tweaks and modifications in some line of code, the entire process can be transferred from one platform to another. Besides, there are various packages like PyInstaller, available to help developers run the code on various platforms.

Wrapping Up

Based on project goals and requirements, there are many programming languages that are handy. However, Python’s simple syntax and readability, ability to develop complex algorithms, rapid testing of ML algorithms, flexibility and visualization support, it presents itself as the jack of all trades for AI & ML development projects.

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