AI vs ML vs DL vs DS
Hi everyone!. We have often seen people getting confused between AI,ML,DL and DS. In this post we will see how these fundamentals differ from each other and how are they linked to each other. So lets dive into it..
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First lets look at each of them separately..
ARTIFICIAL INTELLIGENCE:
Artificial intelligence is a computer concept concerned with building smart machines capable of performing tasks which requires human like intelligence. It is the concept which enables the machines to think of their own.
There are four types of artificial intelligence: reactive machines, limited memory, theory of mind and self-awareness.
Self-driving cars are the best example of AI machines.
MACHINE LEARNING:
Machine learning is a subset of AI. It provides us with some statistical tools to explore and understand about the particular data. It enables machine to learn of their own based on the algorithms provided. Machine learning has three different approaches. They are:
1.Supervised ML - Parse Labelled data
2.Unsupervised ML - Clustering of data
3.Reinforcement learning or Semi-supervised ML - Relearns from errors
DEEP LEARNING:
Deep learning is a subset of Machine Learning. The main idea behind deep learning was the thinking that can we make a machine which learn like we humans actually learn things with the help of brain. Here we create an architecture known as 'multi neural network'. Thus the main idea behind deep learning is to mimic human brain with help of models and multi-neural architectures. DL has different techniques. They are:
1.ANN-Artificial Neural Networks
2.CNN-Convolution Neural Networks
3.RNN-Recurrent Neural Networks
DATA SCIENCE:
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.
Now Hence we understood the basic difference between all. Lets see how they are linked to each other..
CONCLUSION:
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AI machine is a final Product. Machine Learning is a subset of AI as clearly seen in the above picture. Further Deep learning is a subset of ML. Thus all works in coordination to give us the final AI application for use. Finally DS(data science) is a technic which try to apply all these techniques(AI,ML,DL) along with some mathematical tools like statistics, probability, linear algebra, differential calculus ,etc. Thus a data scientist need to have knowledge of all the fundamentals of AI along with mathematical fundamentals.
Hope you learn something interesting from today's blog! Lemme know your thoughts on this topic in the comments..
@projecthope