"K-Nearest Neighbour" is the abbreviation for "K-Nearest Neighbour." It's a machine learning algorithm that's supervised. Both classification and regression problem statements can be solved using the approach. The sign 'K' represents the number of nearest neighbours to a new unknown variable that must be predicted or categorised.
During the training phase, the KNN algorithm simply stores the dataset, and when it receives new data, it classifies it into a category that is quite similar to the new data. Consider the following scenario: We have an image of a creature that looks like a cat or a dog, but we don't know whether it's a cat or a dog.
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Hi Kushal ! Your way of teaching is extremely helpful and you are one of the best teacher in the world.
Extremely helpful and I recommend to my peer as well for this course.
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Aniket Kumar prasad
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Very helpful and easy to understand all the concepts, best teacher for learning ML.
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Rishu Shrivastav
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explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
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VIKAS CHOUBEY
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very nicely explained
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Vrushali Kandesar
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Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
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Juboraj Juboraj
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Easy to understand & explain details.
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Joydeb
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Awesome Course sir and your teaching style is very GOOD.
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Shaga Chandrakanth Goud
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Hi Kushal ji, Thanks a lot for a very good explanation. I have doubts about where we can get the dataset that you explained in the video. Can you make it available in resource ,so that we can downld
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