AI vs ML vs DL vs Data Science
AI vs ML vs DL vs Data Science – Difference Explained
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Welcome to AI Knowledge Desk, In this article will compare and contrast artificial intelligence, machine learning, and data science.

Before moving on, let me ask you two interesting queries:-

  1. Which among the following is not a branch of artificial intelligence?
  • Data Analysis Machine
  • Learning Deep Learning
  • Neural Networks

What is Deep Learning?

First, we will unwrap Deep Learning, and Deep Learning was first introduced in the 1940s. Deep learning did not develop suddenly; it developed slowly and steadily over seven decades. Deep learning was invented made from the 1940s to 2000.

Thanks to companies like Facebook and Google, the term deep Learning has gained popularity and may give the perception that it is a relatively New Concept. Deep learning can be considered as a type of machine learning, and artificial intelligence or AI that imitates how humans gain certain types of knowledge, Deep Learning includes statistics and predictive modeling deep learning makes processes quicker and simpler which is advantageous to data scientists to gather analyze and interpret massive amounts of data having the fundamentals discussed.

Deep Learning
First, we will unwrap Deep Learning, and Deep Learning was first introduced in the 1940s. Deep learning did not develop suddenly; it developed slowly and steadily over seven decades. Theses and discoveries were made on deep learning from the 1940s to 2000.

1.1 Deep Learning

Let’s move into the different types of deep learning:- Neural networks are the main component of deep learning but neural networks comprise three main types which contain artificial neural networks or an convolution neural networks or CNN and recurrent neural networks or RNN artificial neural networks are inspired biologically by the animal brain convolutional neural networks surpass other neural networks when given inputs such as images Voice or audio it analyzes images by processing data recurrent neural networks uses sequential data or series of data. Convolutional neural networks and recurrent neural networks are used in natural language processes speech recognition image recognition and many more.

What is Machine Learning?

The evolution of ML started with the mathematical modeling of neural networks that served. As the basis for the invention of machine learning in 1943 neuroscientist, Warren McCulloch and logician Walter Pitts attempted to quantitatively map out how humans make decisions and carry out thinking processes therefore the term machine learning is not new machine learning is a branch of artificial intelligence and computer science that uses data and algorithms to imitate how humans learn gradually increasing the system’s accuracy.

There are three types of machine learning which include Supervised Learning.

What is Supervised Learning?

Here, machines are trained using label data machines to predict output based on this data.

What is Unsupervised Learning?

Models are not supervised using a training data set it is comparable to the learning process that occurs in the human brain while learning something new.

The third type of machine learning is Reinforcement Learning

What is Reinforcement Learning?

Here the agent learns from feedback; it learns to behave in a given environment based on actions and the result of the action; this feature can be observed in robotics.

Now coming to the evolution of AI, the potential of artificial intelligence wasn’t explored until the 1950s; although the idea has been known for centuries, the term artificial intelligence has been around for a decade. still it wasn’t until British polymath Alan Turing posed the question of why machines couldn’t use knowledge like humans do to solve problems and make decisions we can Define artificial intelligence as a technique of turning a computer-based robot to work and act like humans.

Reinforcement Learning?
Here the agent learns from feedback; it learns to behave in a given environment based on actions and the result of the action; this feature can be observed in robotics.

 

Now let’s have a glance at the types of artificial intelligence weak AI performs only specific tasks like Apple Siri, Google Assistant, and Amazon’s Alexa. You might have used all of these technologies, but the types I am mentioning after this are under experiment. General AI can also be addressed as artificial general intelligence; it is equivalent to human intelligence; hence an AGI system is capable of carrying out any task that a human can strong AI aspires to build machines that are indistinguishable from the human mind.

Both General and strong AI are hypothetical right now rigorous research is going on on this matter there are many branches of artificial intelligence which include machine learning, deep learning, natural language, processing robotics, expert systems, and fuzzy logic, therefore the correct answer for which is not a branch of artificial intelligence is an option a data analysis.

What is Data Science?

Data Science
Now that we have covered deep learning machine learning and artificial intelligence.

Now that we have covered deep learning machine learning and artificial intelligence.

The final topic is data science Concepts like deep learning, machine learning, and artificial intelligence can be considered a subset of data science, let us cover the evolution of data science, the phrase data science was coined in the early 1960s to characterize a new profession that would enable the comprehension and Analysis of the massive volumes of data being gathered at the time since it’s Beginnings data science has expanded to incorporate ideas and methods from other fields including artificial intelligence machine Learning deep learning and so forth.

Data science can be defined as the domain of study that handles vast volumes of data using modern tools and techniques to find unseen patterns derive meaningful information and make business decisions.

Therefore data science comprises machine learning, artificial intelligence, and deep learning.

Thank you for reading and happy learning if you like this article please subscribe to the AI Knowledge Desk website and click next to read similar articles.

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