K Nearest Neighbors – Machine Learning



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Hi , and welcome to the K Nearest Neighbours Course

Are you someone who is new to machine learning ?

Are you someone who wants to get started with machine learning ?

Can you sacrifice 1 McDonalds Meal for this amazing course ?

YES?

Then this course is for you –>

Machine learning which is a buzz word has been in the market for quite some time now . Suppose you are a pizza ?  delivery guy , who has 3 stores A , B and C ,  and want to know which store to visit , or which store is closest to you . This is where KNN , comes in . Imagine you are a dot in the middle and A,B,C are stores . So KNN will help you in determining the closest distance .

Let us look at what you’ll be requiring throught the course –

Materials Required –

  • Mac or Windows
  • At least 4 gb ram
  • Good coding skills
  • Python language
  • Zeal to learn

In this course you’ll learn –

  • What is KNN
  • Machine learning
  • Visualising data
  • Splitting the dataset
  • How to apply KNN
  • Cosine Similarity
  • Confusion matrix
  • Work with really cool datasets and build real time projects

I believe in the concept of “Learn by doing ” and this is emphasised in my class , I myself learn by doing things instead of listening to boring lectures !

You’ll be able to use real time datasets after this class and learn all the necessary components required for getting started with machine learning

Will it be challenging ? YES

Read more course:  Backbone Tutorial Learn Backbonejs from Scratch

Will you get difficulty in understanding things ? YES (if you are a beginner)

But that is what my course is for , it will help you make an app in quick time and you will surely learn many things going forward !

Good luck !

Who this course is for:

  • Students who want to learn the first basic machine learning model
  • Python programmers who want to get into machine learning

K Nearest Neighbors – Machine Learning, Free Tutorials Download

Download K Nearest Neighbors – Machine Learning Free Tutorials Direct Links

Go to Download Tutorials Page Go to HomePage Tutorials

Password : freetuts.download


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