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Nowadays we see a big trends of deep learning and a lot of applications using it . So, I was wondering do people still need to use the classification algorithms (traditionnal machine learning ) ?

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Well, I don't know about all people, but for me, I can say that I first try traditional ML algorithms on a given dataset. I never go for Deep learning directly. Deep learning uses only Neural networks and these can't guarantee to work on every possible data.

There is something known as No Free Lunch theorem - It states that there is no one model that works best for every problem. The assumptions of a great model for one problem may not hold for another problem, so it is common in machine learning to try multiple models and find one that works best for a particular problem.

So, people might not need to use traditional ML, but they should.

deep-learning-vs-classical-machine-learning

https://chemicalstatistician.wordpress.com/2014/01/24/machine-learning-lesson-of-the-day-the-no-free-lunch-theorem/

https://medium.com/@LeonFedden/the-no-free-lunch-theorem-62ae2c3ed10c

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