We humans have progressed so immensely that we made machines who can work for us. In the modern world, this has gone a step further when they work like us by mimicking our actions.
It is made possible only because they are made to think like humans. This splendid phenomenon is what is commonly known as Artificial Intelligence (AI).
If we believe the pundits of technology, the global AI market would grow exponentially in the coming years. As per one estimate, it may grow to more than $180 billion by 2024.
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Industries using Artificial Intelligence
Major industries have already embraced this technology for their operations, which are…
1. Life-Sciences
Artificial Intelligence has definitely entered this field and provided many solutions for healthcare. Mainly there are two areas where AI is useful:
Applications
There are a number of applications available which can help the patient with their day-to-day health problems. If we enlist, they are Babylon, WebMD, ADA and many more.
Operating processes
With the advent of robotics, ground-breaking breakthroughs are expected in the surgeries. There are chances that the surgeon would guide the AI-based robots to operate as it would reduce the chances of infections and it would promote precision.
2. Enterprises
Important AI-based changes are expected in various wings of businesses. They can be in.
Customer Assistance
To answer the basic queries of the customers, chatbots have been created. They are very helpful as they can work during odd hours. Besides, many customers are concerned with the questions which can have automated responses. If the chatbot is able to answer them, there will be less manpower required.
Data Science
For every organization, data science is crucial. It involves data gathering, its analysis, its storage and manipulation. All these are a part of Artificial Intelligence.
3. Academics
Educators have already started experimenting with the tools made of Artificial Intelligence. There are robot tutors who can help the student in learning various aspects of language. They can also assist them in reiteration of tasks.
We can get more information regarding how useful Artificial Intelligence is in a great blog, Major Benefits of Artificial Intelligence in Education by WittySparks.
Eight Reasons To Choose Python For Artificial Intelligence Based Projects
Undoubtedly, Artificial Intelligence is the future of mankind. Most of the developers who work on AI-based projects use Python as a programming language. Let’s look at the reasons behind their preference.
1. Low learning curve
Python is a High-Level programming language. It means that coding of this language is closer to human languages, making it easier to learn and replicate. Developers working in AI-based projects are occupied in building complex algorithms. It would require extensive efforts and considerable time to learn the programming language first.
Python uses the codes which are near to of human languages; as a result, it is more convenient to learn. This would allow them to focus on building the central part of their projects like building algorithms. On top of that, because of its simplicity, these days Python is taught in many universities in the introductory language.
One major reason behind the popularity of this language is the ease in learning it provides. Now, let’s look at the popularity of this language as per TIOBE Index.
TIOBE Index of Popularity of Programming Languages
2. Libraries
A library can be defined as a compilation of routines. There are certain components which most of the applications or websites require. A library has stored these modules or routines as individual objects. Python provides a wide range of libraries which can be very helpful for the users.
Useful Python Libraries:
| Libraries | Usage |
|---|---|
| Numpy | Provides assistance in Machine Learning |
| LightGBM | Provides assistance in building algorithms |
| Keras | Provides assistance in Machine Learning |
| TensorFlow | Provides assistance in Machine Learning |
| Scikit-Learn | Compiles Machine Learning algorithms |
| Weka | Provides a collection of algorithms for data mining tasks |
| Milk | A toolkit for Machine Learning |
| GraphLab Create | Provides assistance in Machine Learning Models |
| Shogun | Open Source Software of Machine Learning |
| AIMA | Python implementation of algorithms |
| Neurolab | a Neural Network Library |
| NLTK | linguistic data for research and development in Natural Language processing |
You can get some more information about Python Libraries from the official web page.
3. Frameworks
A question which confuses the beginners is what the frameworks are. Let’s try to understand it. Many a time, it is observed that we have to build huge and complex applications. They require extensive coding.
We are truly lucky that the majority of websites have similar functionalities and hence; they require similar blocks of code. A Web Frameworks has folders with ready-to-use coding.
This reduces the time and efforts considerably which you require building a website, application or web APIs.
Python is a rich language in the aspect of web frameworks. It has some of the most useful frameworks available. The preferred Python frameworks are…..
- Django
- TurboGears
- Pyramid
- Hug
- Tornado
- Flask
- CubicWeb
- web2py
- Falcon
- Bottle
4. Simplicity
Python offers simplicity, which leads to user-friendliness. It provides ease in mainly two areas:
- Syntax
- Language in Coding
Syntax:
Every Programming language has certain rules which form the structure of that language. They are called the Syntax of that language. Syntax of Python is clean and easy to read.
Language in Coding:
The language used for coding in Python is very near to that of human languages. This makes the coding an easier task in comparison to other programming languages. As a result of this, codes become more readable and understandable.
Along with that, the codes are short as usually they are one-liners. This makes it easy to build, debug and maintain. It has some of the basic codes and their functions. This is especially useful when you have to build complex applications with extensive coding.
5. Platform Independence
There are various platforms available in the digital market like….
- Windows
- iOS
- Linux/Unix
- Android and so on
Python is a cross-platform programming language. The applications which are built using Python can work seamlessly on various platforms.
One of the benefits we can mention here is that this will be inexpensive as it cuts the cost of purchasing a new operating system. Additionally, the developer does not have to get trained for various operating systems.
6. Community Support
Python is the third most popular language, as per the TIOBE survey, 2019. It has been in the market for more than 28 years. Python community has more than 8 million active users.
Community members can help in different ways:
Providing Suggestions:
Whether you are a veteran or a beginner, there are chances that you may face a problem while coding. This is where the community members would come to your aid. You can ask for suggestions which we have observed that they are delighted in providing.
Training:
They can teach the basics of the language to the new developers. Here, we get the learning straight from the experts who are working in the industry. This will be really helpful.
Helping in bug-fixing:
Amongst the community members, we have pros who master in coding. They work as the whistle-blowers. If there are bugs found in existing documents like frameworks, they would bring them to the attention to the authorities and try get them fixed.
These are the ways in which the community helps the developers.
7. Data Science functionalities
Data Science is essential for the Artificial Intelligence as this field is dependent on data manipulation. We are required to deal with the below mentioned functions of Data Science:
- Data Scraping
- Data Acquisition
- Data Processing
- Data Analysis
- Data Manipulation
- Data Visualization
Python is a favorite language for Data Science related tasks.
Python Libraries which are useful in Data Science:
Data Visualization: DeCiDa, Basemap, Matplotlib, Datashader, Cartopy Seaborn, Ridge Map, holoviews and so on.
Data Analysis: Pandas, NumPy, SciPy, and some more.
8. Apt for Machine Learning
Artificial Intelligence is based on Machine Learning which is dependent on Data Science. Acquisition, analysis and manipulation of data is the basic requirement of Machine Learning. Python is a language which is highly suitable for building the functionalities related to Data Science and Machine Learning.
Python boosts productivity and provides stability. As a result, majority developers prefer to use Python for Machine Learning.
Python offers some of the greatest libraries like…
- NumPy – provides assistance for scientific computing and mathematical functionalities
- Keras, and Scikit-learn – provide assistance for machine learning
- TensorFlow – provides assistance for Machine Learning
- PyTorch – an open-source library assisting in machine learning
Apart from the reasons mentioned above, another important reason is its cost-efficiency. It is Open Source. Because of all these reasons, Python is a preferred language for Artificial Intelligence-based projects.
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