10 Reasons Why Python For AI Is A Perfect Fit
It is widely known that the market of Artificial Intelligence is expanding at an astronomical rate. There is speculation that the Artificial Intelligence market would grow to more than $185 billion by 2025. In this blog, we’re going to dive deep into the subject of Python For AI.
So, let’s start the show, right here, right now.!
Python For AI-Based Project
- Industries That Adopted AI
- Why Choose Python For AI?
1. Industries That Adopted AI
There are many industries that have already started using it whereas there are some who are still in the process of embracing it.
If you ask any Python Development Company, they would also agree to that fact, without a pinch of a doubt.! The reason is Python For AI has become a reality.
First, let’s have a quick look at the industries which have adopted this new technology:
This industry definitely benefits from AI. In fact, there are certain institutions that have already started experimenting with small-sized robots. These robots perform the task of a tutor.
There are various fields where these tiny wonders can help students like linguistics, social behavior, basic calculations and so on.
One of the benefits it provides is, it can help specially enabled children.
There are certain online platforms available that allow students in building quizzes which would help them in studies.
Many research studies conducted to predict the future usage of AI.
As per one of the studies, by 2025 the usage of AI in the education field will be increased by 37.2%.
The technology will be used in the continuum starting from basic education to the highest level.
1.2 Customer Services
Chatbots are proving to be a great help for various industries as they are able to provide information to the customers. There are mainly two benefits of having a chatbot:
- It provides a lot of conveniences because it can even work during odd hours. There are still many industries that do not provide customer service 24*7.
- So, for the window where humans are not around, chatbots can take over and answer at least the basic level queries.
- It provides the possibility of employing fewer numbers of employees.
1.3 Talent Procurement
AI can prove to be a boon for the Human Resource department. They get a lot many job applications for a particular role especially if it is an esteemed organization.
There are some AI applications that can scan resumes and job profiles of the candidate.
They can find the keywords from the mentioned criteria which match appropriate candidates for the role by wading through the unfitting ones.
It only takes friction of seconds to find suitable candidates.
There are some AI software developers who create AI-powered systems. These installed software would understand the surroundings and navigate the vehicle as per it.
Different types of sensors are already being used which would replace human efforts to a great extent. That’s why Python For AI can be a great boost to the automotive sector.
In the field of health care, AI is being used extensively. There are many apps available like WebMD, K health, Babylon, ADA and so on which help the patients with their queries related to symptoms. It even provides them with medical advice.
These are just a few industries that use AI. Now, let’s talk about the reasons for Python being the first choice of developers of AI.
2. Why Choose Python For AI?
2.1 Backbone of Libraries & Frameworks
A library consists of the routines which are required by most of the websites. These routines or modules are stored as individual objects. They are precompiled in a library.
Users can access them for either referencing or borrowing. However, a Framework has readymade codes which can be used as per the requirement.
Python offers some of the most amazing libraries as well as Frameworks which are helpful from the perspective of Machine Learning.
For knowing more about this subject, read the Guide of Python Development. It will help you in the long run.
Python Libraries and Frameworks which are helpful in Machine Learning:
|Libraries and Frameworks For Machine Learning||Details|
|GraphLab Create||An end-to-end Machine Learning platform which helps in building ML models|
|Numpy||A library to aid Machine Learning|
|MDP-Toolkit||A collection of supervised and unsupervised learning algorithms|
|Scikit-Learn||Python module integrating classic Machine Learning algorithms|
|LightGBM||A library assisting in constructing new algorithms|
|Milk||A Machine Learning toolkit|
|Keras||A library to aid Machine Learning|
|TensorFlow||A library to aid Machine Learning|
|SOM (Self-Organizing Maps)||A form of Machine Learning technique which employs unsupervised learning|
|Weka||A collection of Machine Learning algorithms for data mining tasks|
|PyBrain||A modular Machine Learning Library|
|Orange||Contains Components for machine learning|
|Shogun||Machine Learning Open Source Software|
Python Libraries which are helpful in General Artificial Intelligence, Natural Language & Text Processing and Neural Networks:
|AIMA||Python implementation of algorithms|
|pyDatalog||Logic Programming engine|
|NLTK||Python modules on linguistic data and documentation for research and development in natural language processing|
|Gensim||framework designed to automatically extract semantic topics from documents|
|Neurolab||a simple and powerful Neural Network Library|
|Ffnet||fast and easy-to-use feed-forward neural network training solution|
There are some useful Libraries and important Frameworks provided by Python which can be learned from the official web page. So, people should consider Python For AI.
2.2 Simple Design
Python has a very simple design. Some of the basic rules which we call syntax are truly easy to follow. Even the basic unit of programming – the code is also short in comparison to others.
Programmers prefer to devote their time in building complex algorithms. At this stage, they would surely not prefer getting bogged down by complexities of the lengthy codes and complicated rules which are difficult to understand, remember and follow.
There are mainly two areas which make this language simple, compact and user-friendly:
Clean and Clear Syntax
Any programming language has a particular syntax which rules to be followed while developing any program. These rules will provide information about how a program will be developed and executed. Python’s syntax has some characteristics as mentioned below:
- The syntax is clean and without complication.
- If we wish to review the script written by either us or someone else, we can do that without much hassle.
It has some resemblance to the syntax of Java, C, and Perl. Still, there are some conspicuous differences. These differences make Python more readable.
Python is designed as a High-Level language. What this means is the language used for building the codes matches the language spoken by humans. There are certain benefits to this feature:
- Codes become more readable.
- They become understandable.
- It becomes less complex and easy to follow.
On top of simplicity, there is another benefit of length it provides. Most of the codes are written in one line. As there are no long chains of codes, they are easier to develop.
Because of the simplicity, less length and understandability, AI developers prefer Python For AI. In AI, there are long and complicated routines and algorithms to be followed.
Python helps in reducing the pain of the developers by offering the benefits of compact codes.
To sum, we can say that Python is easy to understand and follow.
2.3 Quick Start & Early Exposure
Python comes in the second position in the area of programming languages which are easy to learn. It is preceded by only HTML.
There have been a number of reasons which make it one of the favorites for the programmer to learn it. It uses shorter codes that are readable, understandable and close to human languages.
In addition to that, even the syntax is easy to follow. These advantages make Python a great choice for beginners.
With AI, complex algorithms can be built. If the developers do not intend to put intensive efforts in learning new programming language as they are already occupied with the complex algorithms to be produced, they can start with Python which is easy to learn.
The other reason behind its wide application is these days Python is taught in many of the high schools and universities. If this course is taught with the initial education, they are well exposed to the programming language.
All over the world, there are many institutions that either teach Python as introductory language or have to incorporate d it in the curriculum.
Below are some of the High Schools which have included Python in their curriculum:
- Model Experimental Senior High School of University of Macedonia – Thessaloniki, Greece
- Duchesne Academy of the Sacred Heart – Houston, TX
Below are some of the universities where Python is used extensively in their curriculum:
- University of New South Wales, Australia
- The University of Toronto, Canada
- University of Waterloo, Canada
- Zhejiang University, China
- Universitat Politècnica de Catalunya (UPC), Spain
- The University of Oxford, United Kingdom
- University of California, United States
- Wartburg College, United States
2.4 Freedom of Selecting the Platform
There is no requirement of sticking to a particular platform because Python can work seamlessly on any given platform. Various platforms available in the market as mentioned below:
Different developers have different requirements and comfort zones. It is difficult to come down to just one platform which would be suitable for all.
Various components of Python application can be created on various platforms and they can be accessed and worked upon cross-platform.
If it is a huge organization and there are multiple developers working on the same project, they can work on their individual systems and their work can be incorporated in the main system at a later stage.
2.5 Assistance of the Community
At the time of writing this, there are more than 8 million users of Python worldwide. There are 1,50,000 active web sites that use Python.
As mentioned earlier, the biggies like Google support this language. It provides immense support in the form of training and documentation.
Apart from the web giants, even the individual web developers are there to provide assistance. There are some areas where they help the beginner or even an experienced developer:
Learn the Basics
The community members offer to teach the basics of Python to the beginners of the language. This is a great way of learning as this would be
Assistance With Regard to Coding
Whether the novice or an expert, you may get stuck at a stage in coding. This is when the community comes to your aid. There are many Python Web Development Frameworks that can help you in this regard as well.
Veteran developers who might have passed through the same stage. Based on their experience, they can guide or suggest what should be your next step.
Bug Identification and Escalation
The existing Python Libraries and Framework may have some bugs or while working because of incorrect coding we may encounter bugs.
They are dangerous to the development of the further program as well as execution.
The community members assist in identifying the bugs, fixing the bugs and if there is a requirement, escalating the bug too.
Thus, community members help in numerous ways.
Python language has a highly accommodating nature & it’s highly flexible.
It allows the developers to select their preferred way of programming.
You can also select whether they want to go ahead with Object-Oriented Programming or scripting.
It not only lets the developers choose their preferred style of programming but even offers the option of combining these styles.
Let’s look at the different programming styles:
The Procedural Style
It is very popular with beginners. In this type of programming, tasks are treated as step-by-step instructions.
The program has the list of such instructions which would direct the computer.
This is mainly used for iteration, sequencing, modularization, and selection.
The Imperative Style
Imperative word in general English means giving a command.
In this type of programming, commands are given to the computer.
They direct the computer about how it should perform these tasks.
The sequence of computations is described in this style.
The Functional or Declarative Style
It announces which operations should be performed.
This declaration takes place in the form of mathematical equations.
The Object-Oriented Style
It encompasses many concepts like object, class, Encapsulation, Abstraction and many more.
Similar objects belong to the same class.
This style can be used to a certain degree as it is not supported in totality.
The most significant benefit of this feature is, it lets the developers work in their comfort zone which makes their work less prone to errors.
2.7 Combining With Other Programming Languages
Python can seamlessly combine with other languages. In fact, that is the reason because of which it is called the glue language.
Different developers have different preferences in the matter of the language they select for programming.
If there is a big project which encompasses the work of different programmers, it is difficult to make them work using a common language.
This is the time when Python comes to our aid. Developers can work in languages that provide them comfort.
Then these blocks of work from various languages can be stuck into a common canvas of Python. That’s why Python For AI can be a perfect combination.
As per the official web site, it can integrate with other languages to create large and complex applications and also expect an expectancy of a long life.
2.8 Suitability for Machine Learning
Python has gained a lot of importance in the field of AI because of the services it provides for Machine Learning. AI is based on Machine Learning.
It help us in studying Machine Learning related data Machine Learning. Acquisition Manipulation and Analysis of Data are the pillars of Machine Learning.
A lot of programmers who work on Machine Learning, use and prefer Python as it offers stability. Apart from that, it helps in improving productivity.
In sum, Python is the preferred choice for Machine Learning which is the base of Artificial Intelligence and Machine Intelligence.
2.9 Assistance in Data Science
We need to deal with data in order to achieve fruitful results of AI. Data science assists AI in figuring out the solutions to complex problems by associating resembling data for future use.
It allows the AI to look for appropriate information from the huge pools in a rapid manner and with more efficiency.
Developers use Python for managing Data functions such as Data Scraping, Data Analysis, Data Visualization and many more. Hire Python App Developers from a reputed firm to know more about these things.
On top of that, there are some of the most important libraries which can help us in achieving various tasks related to data. Some of these useful libraries are Pandas, SciPy, NumPy, Seaborn, Matplotlib and so on.
Any web project involves a certain amount of cost for development as well as maintenance. AI is no exception.
It will be of great benefit if we are able to use a programming language to build an AI project which does not make a dent in our pocket.
Python is an Open-Source programming language. Hence, it is free to use. There is no cost for acquiring the license for the same.
On top of that, there are some really amazing frameworks and libraries available that would assist us further with regard to the development of our project.
Summing Up Things
Python is a highly efficient language with many features that make it an ideal choice for the Artificial Intelligence project.
In recent times, Python For AI has become a huge attraction.
We hope you had a great time reading this article. Thank You.!
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