Machine Learning Tutorial 13 - K-Nearest Neighbours (KNN algorithm) implementation in Scikit-Learn

Description: In this video, we'll implement K-Nearest Neighbours algorithm using scikit-learn. The K-nearest neighbors (KNN) algorithm is a type of supervised machine learning algorithms. KNN is extremely easy to implement in its most basic form, and yet performs quite complex classification tasks. It is a lazy learning algorithm since it doesn't have a specialized training phase. Rather, it uses all of the data for training while classifying a new data point or instance. KNN is a non-parametric learning algorithm, which means that it doesn't assume anything about the underlying data. This is an extremely useful feature since most of the real world data doesn't really follow any theoretical assumption e.g. linear-separability, uniform distribution, etc. Blog reference - stackabuse.com... About Me - Website: rounakvyas.me GitHub: github.com/its... LinkedIn: / itsron143

[@tlubaina]

It's been more than 5 years since I am following your channel through different phases of my career. You always ace it and I wanted to let you know that there was not a single time when your videos didn't help me in the past 5 years. Thank you for all the work. You are the best teacher I've ever had

[@siyamul_islam]

whole world using same dataset, same procedures ! how funny! Even some phd holders using same example! they Don't have minimum creativity!

[@Borzacchinni]

Many create tutorials before being good at the craft. Also seen by the lack of explanation from many of these Iris tutorials

[@GenoTechno]

White Gary Miller Helen Thomas Robert

[@Ben-tm7nt]

Best explanation bro... You deserve 1 million subs

[@VOGTLANDOUTDOORS]

NICELY DONE...
... but I DID notice that you DIDN'T actually USE your newly-trained predictor on a SINGLE test X (vector) - this too is a common scenario, as not everyone uses kNN for classifying BATCHES of inputs ;-) ...
A SINGLE test vector would take on THIS shape:
test_x_2 = [[5.9, 3.0, 5.1, 1.8]]

[@Miiifaco]

Hi, Have you ever implemented SVM and Linear Regression via python,too? And put it on your channel?

[@shahzebkhan794]

scaler.fit(x_train) is giving numpy.ndarray error. not resolving on using [ ]

[@101marsi]

Did you figure it out? I keep getting an error on that as well

[@nafassaadat8326]

I did not understand what was the final output how it classify the object that in which classes it belongs??

[@pressiyamu2187]

He could have done a better job of explaining it I agree

[@rubyglossy]

i agree to

[@shubhamsahai2492]

Thank you very much for a very well taught and presented video..

[@sapnaarora9546]

How can we visualise the graph for the same? Kindly explain

[@ehraazqureshi1285]

plot using matplot.lib.pyplot function

[@wanted_edits]

thanks, also thanks for brain malfunction and hearink keyboard sounds 24/7 lol

[@HYroglif]

Thank you so much for this tutorial, however, every tutorial I've seen utilizes the Iris dataset and real-world data does not come anywhere near that. Could we get another example please?

[@kabijoshi5949]

you can only give algorithms or provide some logic behind all those.

[@LuisOrtega-ue1vp]

I keep getting a ValueError when trying to run the Preprocessing Block of code. any suggestions?

[@agitacademy]

The audio on the video is very low... pls try and adjust that

[@HappyMishra1703]

I am unable to find the dataset where it is can anyone share in the comment section

[@shlokdoshi7162]

If a give an input list for the KNN algorithm to predict the classes of each element, How can I print out the list of inputs only belonging to a particular class?

[@VSaipavankumarReddyLE]

Civil related data using prediction values

[@VSaipavankumarReddyLE]

Bro please knn tool new version videos

[@pallavishnuvardhan2361]

How can a new data point be pointed using previous data set??

[@furkanhacbebekoglu6885]

grafik lazım o nerede?

[@rohiniyadav9287]

Blur video

[@shilpatadas7152]

Thanks 🙏

[@vishnuvandanapyatla2888]

Can u post the link for the dataset ?

[@vitoluong7524]

I really appreciate your work on this, but I do hope you add subtitle to this and the upcoming videos.

[@hi19799]

good explanation

[@malKav05]

Thank you so much for this! It's really helpful and easy to follow!

[@sachintendulkar9817]

How can we visualise the graph for the same? Kindly explain

[@LatpateShubhamManikrao]

that helped loads .thanks

[@jayeshpobari6565]

which language is better nd more job... c# or php ... pls say me nd say me reason why better it ...

[@samarmohan9891]

C#, because PHP is getting old. C# can be used for so much and is backed by microsoft

[@samarmohan9891]

it is train_test_split

[@musicalgames935]

Ausome tutorial

[@adhvaithstudio6412]

please explain the hyper tuning parameters as well

[@fingerfighters9999]

I dont understand this video ..infact i dont even know M of machine learning :/