Differences between AI,ML, DL

People reading this are for sure techies who love to play with Data or work with statistics or Data Science aspirants just like me :)! Voila!!! we are sailing in the same boat then :)!

When I was a machine learning noob a year back, even I had this biggest doubt . What is the difference between Machine Learning, Deep Learning and Artificial Intelligence?????

And I am sure many of you who are reading this right now also have the same exact question. Let me help you and explain you the difference in a simple way.

Let me tell you, all the three might look similar but can do different actions!

Remember there are many other differences other than the mentioned if we dive deep down into all these three but I want to simplify the process of understanding the differences for every noob so that every noob can explore further with clear understanding.So I have used simple language to help you understand other than using heavy technical terminology.

If we consider AI as a larger bucket then Machine Learning is the sub bucket of AI and again DL is the sub smaller bucket of ML as shown above.

ARTIFICIAL INTELLIGENCE

1. Artificial Intelligence is a combination of ML, DL and many other concepts.
2. Artificial Intelligence is a larger bucket which deals with intelligent machines which can mimic or simulate human behavior.
3. We can create Artificially intelligent machines by using external programming.

Applications :- Robots,etc.

Where as ML and DL follow different methodologies yet similar step by step procedure :

1. Take data

2. Preprocess the data

3.Train the machine

4.Test the machine with new data

But at every step two of them differ :D!

MACHINE LEARNING

1. Take data in the form of raw data(datasets).
2. Preprocess the data by using python(preferred) inbuilt functions and by applying few statistical methodologies.
3. Train the ML model using statistical methods.
4. Draw inferences and conclusions from the model built by testing the model on new data.

Applications :- Regression, Classification, Prediction,etc.

DEEP LEARNING

I am explaining you in terms of images here but using deep learning we can take any specific kind of data like voice data, image data,etc. So Deep Learning can be used for specific purposes.

1. Take data in the form of images(image datasets).
2. Preprocess the images (example :-properly resizing all the images to same size).
3. Train the DL model using neural networks.
4. Test the model on new image datasets.

Applications :- Image Classification,Speech Recognition,etc.

CONCLUSION

1. AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas,
2. Machine Learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly and
3. Deep Learning is a subset of machine learning which focus on data of specific form and neural networks.

Hope now the readers are clear about the differences :) Find other useful blogs in my publication “https://medium.com/life-in-data-science”.

Happy Learning! :)