* Cantinho Satkeys

Refresh History
  • FELISCUNHA: ghyt74  pessoal  4tj97u<z
    21 de Abril de 2025, 10:38
  • cereal killa:
    19 de Abril de 2025, 21:17
  • j.s.: tenham uma Santa e Feliz Páscoa  49E09B4F 49E09B4F 49E09B4F
    19 de Abril de 2025, 18:19
  • j.s.:
    19 de Abril de 2025, 18:19
  • j.s.: dgtgtr a todos  4tj97u<z 4tj97u<z
    19 de Abril de 2025, 18:15
  • FELISCUNHA: Uma santa sexta feira para todo o auditório  4tj97u<z
    18 de Abril de 2025, 11:12
  • JPratas: try65hytr Pessoal  4tj97u<z classic k7y8j0
    18 de Abril de 2025, 03:28
  • cereal killa: try65hytr malta  classic 2dgh8i
    14 de Abril de 2025, 23:14
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  101041
    13 de Abril de 2025, 11:45
  • j.s.: e um bom domingo de Ramos  43e5r6 43e5r6
    11 de Abril de 2025, 21:02
  • j.s.: tenham um excelente fim de semana  49E09B4F
    11 de Abril de 2025, 21:01
  • j.s.: try65hytr a todos  4tj97u<z
    11 de Abril de 2025, 21:00
  • JPratas: try65hytr  y5r6t Pessoal  classic k7y8j0
    11 de Abril de 2025, 04:15
  • JPratas: dgtgtr A Todos  4tj97u<z classic k7y8j0
    10 de Abril de 2025, 18:29
  • FELISCUNHA: ghyt74  pessoal   49E09B4F
    09 de Abril de 2025, 11:59
  • cereal killa: try65hytr pessoal  2dgh8i
    08 de Abril de 2025, 23:21
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  43e5r6
    06 de Abril de 2025, 11:13
  • cccdh: Ola para todos!
    04 de Abril de 2025, 23:41
  • j.s.: tenham um excelente fim de semana  49E09B4F
    04 de Abril de 2025, 21:10
  • j.s.: try65hytr a todos  4tj97u<z
    04 de Abril de 2025, 21:10

Autor Tópico: K Nearest Neighbors : Machine Learning  (Lida 89 vezes)

0 Membros e 1 Visitante estão a ver este tópico.

Online mitsumi

  • Moderador Global
  • ***
  • Mensagens: 119261
  • Karma: +0/-0
K Nearest Neighbors : Machine Learning
« em: 08 de Julho de 2021, 11:58 »
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 371 MB | Duration: 1h 8m

What you'll learn
K Nearest Neighbours Algorithm
Machine Learning
Data Science
Requirements
Python programming
Basics of machine learning
Zeal to learn
Not be able to eat 1 Pizza
Description
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

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

Screenshots


Download link:
Só visivel para registados e com resposta ao tópico.

Only visible to registered and with a reply to the topic.

Links are Interchangeable - No Password - Single Extraction