This step-by-step guide takes you through the use of Artificial Intelligence with Python. The blog gives a brief and basic concept of AI at the outset, and moves on to outlining things like the need to learn AI, what’s involved in AI, and why Python is a good choice for AI. We also talk about various types of AI to end the discussion.
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Python is an open-source language that has gained a lot of popularity in recent times because of its advancements in fields of artificial intelligence and image processing. Today we will talk about using Python With Artificial Intelligence.
It is simple to learn, and it is a high-level language. Various packages are available in Python, using which you can easily perform complex tasks such as data gathering, data preprocessing, data cleaning, applying AI-based algorithms, etc.
In this article, we are going to clear all your doubts regarding AI. We are going to discuss various libraries available in python. Also going to debunk the common myth that AI (Artificial intelligence) and ML (Machine Learning), and DL (Deep learning) are all the same.
We will be discussing various learning methods and the algorithms typically implemented in a certain model of learning. You can Hire Python Developers to develop such solutions.
Basic Concept Of AI
The concept of Artificial Intelligence is very simple – the computers should be able to do what humans are doing. And it does that by learning.
We give a lot of data to AI systems to make it understand how to make decisions. Now when next time, the system gets similar data, based on previous learning it will give you answers.
Let me clear this with a very simple example. When you were born, were you able to classify between apple and orange? Probably, not. Only after you learned in school or your parents taught you, you were able to classify it.
In this ever-changing world of technology, AI has now become a necessity to learn to excel in your life. There are various reasons for this:
AI can read a lot of data and analyze it
With the amount of data we are dealing with currently, it is impossible to manually derive relevant information from it. This is where AI helps to get relevant data as well as insights from that data.
The amount of data is increasing
And even if you are able to get insights from the data you have currently, remember the data will keep on increasing, and at one point, it would become impossible for you to analyze it.
You can achieve accurate results
The accuracy of AI-based algorithms can be increased with more data. With continuously evolving data, you would get better results with AI rather than doing it manually.
AI can help you organize your data
The most tedious task is to classify the data. Don’t worry, AI can help you here. Once you give the system a labeled data, it will learn and start classifying the data next time it gets it.
AI can learn by itself
There are instances when the data keeps changing and normal algorithms don’t work. But with recent advancements in the field of AI, scientists are able to come up with models that can learn important characteristics on their own.
Humans can take a lot of time to collect data and derive insights. But once you have trained the AI model, it can help you get insights into your data in real-time and enable you to make quicker decisions. So, Artificial Intelligence with Python can be great.
AI is a very vast field and there are many subfields involved in it. We will discuss the most important fields present in it.
It is one of the most relevant fields among all other presents in the field of AI. Most of the research since 1980 has revolved around machine learning.
In machine learning, we identify important parameters or features that are present in data and try to apply algorithms on top of those features.
Let’s take a simple example. You are given a data set of human beings with fields as age, name, address, education, and other relevant information. And you have to find their expected earnings.
In the field of logic programming, scientists use methods to enable machines to do reasoning based on the data.
In this, logic is represented by the knowledge and it is manipulated using inference. It is used in segment analysis and code analysis. So, Artificial Intelligence Python is awesome.
The term fuzzy logic was coined in 1965 by Lotfi Zadeh. He introduced a new theory called the fuzzy set theory.
It uses a concept that people don’t take decisions based on precise and exact numerical information that is available.
This vagueness is represented using mathematical models in fuzzy logic. This allows you to build models that can support this vagueness and let you represent, manipulate, and interpret model data.
Since 2010, neural networks have gained a lot of popularity and is an emerging promising new field in AI. We just saw in machine learning how to identify the important features.
The neural network takes this one step ahead. It identifies important features by itself and applies algorithms on top of that.
Natural language processing is a field that deals with text, speech, and language. It builds models based on the above input. So, Artificial Intelligence with Python can be awesome.
Recently Google has launched a very good NLP based algorithm called BERT which identifies various speech patterns. It was used to build an application, which was able to generate songs on its own.
It is a mix of supervised and unsupervised learning. In Reinforcement Learning, initially, you provide it with a list of data that are labeled.
You will also provide data, which doesn’t have labels. The model will then analyze both the data and then derive important features from it and build the model.
Python has a wide range of libraries that are available directly. You just need to add code to prepare data and provide it to the model.
All the major algorithms that are currently used in the market are available as a prebuilt python library. You just need to add these libraries and you are all set for deriving insights from it.
All the new algorithms that are becoming famous come along with a prebuilt python library which has the algorithm code. This allows you to experiment rapidly with newer algorithms that are coming on the market.
All the python libraries designed for AI have a similar interface. The way they clean data, apply algorithms, and provide you with insights are almost similar in all the libraries. This allows you to learn the code quickly and become productive.
Python language is platform agnostic. You can run the same code on Windows, Linux, or Mac. This allows you to port your code easily among different platforms.
Python has a very big community and it is very supportive. You can quickly get answers to all the questions you have. You also get code samples.
There are various blogs also present on various social media platforms which discuss in detail implementation for various algorithms also.
Artificial narrow intelligence or also known as Weak AI focuses on one specific topic. It takes one problem and works on it. For instance, it tries to solve a chess game or analyze the raw data to determine specific insight.
It operates with a specific mindset. It does not consider human emotion or tries to mimic the exact step which a human would do. Most of the AI algorithms that are running in production are currently narrowed AI.
Google Siri, Amazon Alexa is all based on weak AI because they execute a specific task. Though these applications are powerful, they are still a weak AI as they are not as good as humans. They lack self-awareness and consciousness and cannot replicate the human mind.
Artificial general intelligence, or also called as Strong AI, is as smart as human beings. They can perform all the actions that any human being can do. For instance, as shown in sci-fi movies like “Her” or web-series like “Upload”.
We have not yet been able to achieve this kind of awareness like artificial general intelligence but hopefully, in the near future, we should be able to do it.
As humans, we can think and strategize and take decisions, but machines are not able to think like humans. Artificial Intelligence Programming with Python is a possibility.
An Oxford professor defines artificial super intelligence as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest”. The computers would be able to perform much better than any human being.
This is particularly raising fears among the people and they feel they would not be able to control the computers once the computers become more smart and intelligent. So, Artificial Intelligence with Python can be massive.
The above image will clarify all the misconceptions:
Basically, all three are interconnected fields. Machine Learning and Deep Learning provides you with specific insights into data and allows you to make data-driven decisions by giving you algorithms. That’s why Artificial Intelligence Python is a great combination.
We would try to list important python libraries that you can use to build a model. This can help you in using Python With Artificial Intelligence.
Artificial Intelligence is an emerging field and newer algorithms are being devised every day. It is really important for you to learn about AI as it has many advantages over traditional methods of deriving insights.
Python With Artificial Intelligence is the most suited programming language when it comes to the field of Artificial Intelligence.
The code written in python is not only easy to use but at the same time, there are multiple libraries that are available which can be directly used to create models and get data.
Also, since all the libraries written in python use a similar interface, you can rapidly experiment with them and use the one which provides you with high accuracy.
We have also discussed how Artificial Intelligence with Python is great. We hope you had a great time reading this article and it proves to be of great interest to any Python Development Company. Thank You.!
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