Why is Python Programming Better for AI?

 

Gone are the days when JavaScript and HTML were considered the most reliable programming languages. Nowadays, the demand for Python for artificial intelligence and machine learning projects is growing rapidly. AI is all set to transform the world into a digital place where machines can automate nearly every human task. Spotify and Netflix are the best examples of AI algorithm. These apps offer song and movie suggestions based on the user’s browsing history.

As artificial intelligence is revolutionizing the world, more and more companies are planning to implement AI-based applications. With the growing demand for artificial intelligence, there comes a requirement for a coding language. The easier the programming language you choose, the faster you can develop the AI projects. That’s when Python comes into the picture. Considering its simple and effective syntax, it isn’t surprising to say that this programming language has become one of the best options for AI and ML. In this post, we are going to discuss the top benefits of using Python for AI.

· Vast Library for AI

One of the main reasons why Python is your ultimate choice for AI projects is its vast library. The programming language comes with the base-level items that are designed to help you code in a quick and efficient manner. Not only do they save you a lot of time on coding, but these libraries enable users to manage a large volume of data. The python libraries that make coding easier for the users are Pandas, Caffe, Scikit-learn, and Keras.

· Good Readability

The simple syntax and readable codes make Python a perfect option for beginners. If you are planning to learn a new programming language, then Python is your ideal option. Artificial Intelligence involves complex machines and sophisticated processes. Complex programming languages make it harder for the developer to achieve the development goals.

Python is an easy-to-read programming language. It makes it easier for the user to type lengthy codes. The sooner you are done with the coding, the faster you can test the algorithms and implement them. Besides that, an easy and readable programming language is a must when the project is managed by a group of developers.

· Great Community Support

This open-source programming language has gained a lot of attention over the past few years. Hundreds of thousands of developers have learned Python for software development, website designing, and other applications. That being said, rest assured that there is a professional and trained python community at your disposal (if you ever need help). They can guide you throughout the development process. You could find many Python tools, libraries, and documentation for free. You can talk to the professionals and Python experts to fix technical issues.

· Visualization Options

Python is known for its vast range of libraries and the visualization tools that make it a flexible and versatile programming language for artificial intelligence. No matter how complex the project is, Python can help you to accomplish your objectives.

What is the Difference between Machine Learning and Artificial Intelligence?

 

Machine learning and artificial intelligence have become a major trend these days. Both terms are used interchangeably. It is important to note that artificial intelligence and machine learning are two different concepts. Machine learning is a part of AI, while the latter is a broader concept that involves machines to automate the challenging tasks. AI is used in almost every industry. The best example is the online eCommerce shopping website, such as Amazon. It has implemented the AI algorithm to discover the customer’s buying history and offer them suggestions based on what they will be interested to purchase.

Contrary to the popular belief, AI isn’t new. In fact, it has been around for decades. Artificial Intelligence gained popularity after the first logical computer was launched. It had the ability to do arithmetic calculations, store data, and perform other basic tasks. However, machine learning and AI has garnered a lot of attention over the past few years. As technology is progressing, the developers are launching new devices and technical gadgets that are engineered to automate human tasks. The automated vehicles and online stock trading are other common examples of artificial intelligence.

Machine Learning Vs AI

Machine learning, on the other hand, is defined as the machine’s ability to function without being programmed. Unlike the outdated computers, the latest technical devices are designed to perform an extensive range of functions without human intervention. You don’t need to program this machine. In fact, these machines are smart enough to handle a large volume of data efficiently. Note that artificial intelligence is used to provide machines with the ability to learn from data. Machine learning is part or subset of the AI.

To put it in simple terms, AI can create machines that mimic humans. These machines can perform research, manage data, and find the required information seamlessly. As mentioned above, the machines do not need human intervention. You don’t have to program them. They use the data and algorithms to perform the basic tasks efficiently. What sets these machines apart from the standard computers is their unique ability to make predictions based on the statistical and qualitative data. They use a large volume of structured data to help people make sound decisions.

Siri and Alexa are the machines that run on AI algorithms. They extract information from the internet and complete the requested task using the data. Artificial intelligence focuses on developing smart solutions that can mimic human functions efficiently, while machine learning is based on the machine’s ability to learn from the data and experiences. These machines are made to carry out the requested tasks as efficiently as possible. While these advanced systems have the ability to perform tasks like a human, they have a limited scope. Machines cannot perform complex tasks. They can be used for the operations they are designed for. The best examples of machine learning tools are Google Search Algorithms, Amazon auto-recommendation feature, Facebook auto-tagging system, and more.