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K Nearest Neighbors Machine Learning [CoursesGhar]

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English

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371.09 MB

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08-07-2021 11:53

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File	Size
!! IMPORTANT Note !!.txt	287.00 B
!!! Please Support !!! [CoursesGhar.Com].txt	197.00 B
00. Websites You May Like/CoursesGhar.Com.url	114.00 B
00. Websites You May Like/New Internet Shortcut.url	114.00 B
1. K Nearest Neighbors [CoursesGhar.Com]/1. What is KNN-en_US.srt	4.08 kB
1. K Nearest Neighbors [CoursesGhar.Com]/1. What is KNN.mp4	14.26 MB
1. K Nearest Neighbors [CoursesGhar.Com]/2. More about KNN-en_US.srt	2.93 kB
1. K Nearest Neighbors [CoursesGhar.Com]/2. More about KNN.mp4	9.54 MB
1. K Nearest Neighbors [CoursesGhar.Com]/3. How does KNN Work-en_US.srt	4.83 kB
1. K Nearest Neighbors [CoursesGhar.Com]/3. How does KNN Work.mp4	21.77 MB
1. K Nearest Neighbors [CoursesGhar.Com]/4. KNN Working-en_US.srt	4.75 kB
1. K Nearest Neighbors [CoursesGhar.Com]/4. KNN Working.mp4	21.58 MB
1. K Nearest Neighbors [CoursesGhar.Com]/5. Advantages of KNN-en_US.srt	2.38 kB
1. K Nearest Neighbors [CoursesGhar.Com]/5. Advantages of KNN.mp4	8.07 MB
1. K Nearest Neighbors [CoursesGhar.Com]/6. Disadvantages-en_US.srt	2.15 kB
1. K Nearest Neighbors [CoursesGhar.Com]/6. Disadvantages.mp4	8.31 MB
2. Setting up [CoursesGhar.Com]/1. Working Environment.mp4	38.30 MB
3. Project - Basics [CoursesGhar.Com]/1. Importing Data-en_US.srt	5.38 kB
3. Project - Basics [CoursesGhar.Com]/1. Importing Data.mp4	23.91 MB
3. Project - Basics [CoursesGhar.Com]/2. Visualising the data-en_US.srt	3.43 kB
3. Project - Basics [CoursesGhar.Com]/2. Visualising the data.mp4	11.55 MB
3. Project - Basics [CoursesGhar.Com]/3. KNN implentation-en_US.srt	5.66 kB
3. Project - Basics [CoursesGhar.Com]/3. KNN implentation.mp4	28.17 MB
3. Project - Basics [CoursesGhar.Com]/4. Output-en_US.srt	3.00 kB
3. Project - Basics [CoursesGhar.Com]/4. Output.mp4	10.49 MB
3. Project - Basics [CoursesGhar.Com]/5. Prediction-en_US.srt	3.35 kB
3. Project - Basics [CoursesGhar.Com]/5. Prediction.mp4	12.28 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/1. Importing data-en_US.srt	2.66 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/1. Importing data.mp4	46.59 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/2. Training and testing data-en_US.srt	6.33 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/2. Training and testing data.mp4	20.90 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/3. Scaling-en_US.srt	2.98 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/3. Scaling.mp4	8.40 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/4. Implementing algorithm-en_US.srt	2.54 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/4. Implementing algorithm.mp4	8.61 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/5. What is confusion matrix-en_US.srt	8.83 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/5. What is confusion matrix.mp4	33.53 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/6. Confusion matrix-en_US.srt	3.99 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/6. Confusion matrix.mp4	15.74 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/7. What is accuracy-en_US.srt	2.94 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/7. What is accuracy.mp4	10.04 MB
4. Project - IRIS Dataset [CoursesGhar.Com]/8. Accuracy-en_US.srt	1.18 kB
4. Project - IRIS Dataset [CoursesGhar.Com]/8. Accuracy.mp4	5.51 MB
5. Conclusion [CoursesGhar.Com]/1. Thank you-en_US.srt	984.00 B
5. Conclusion [CoursesGhar.Com]/1. Thank you.mp4	13.45 MB
More !!! Courses.url	114.00 B
telegram @coursesghargate.url	128.00 B
Uploaded by [Coursesghar.com].txt	1.10 kB

Description

K Nearest Neighbors Machine Learning [CoursesGhar]
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz Language: English | Size: 371 MB | Duration: 1h 8m
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Implement KNN using Machine learning
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 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 deteing 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 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 datasets after this class and learn all the necessary components required for getting started with machine learning
Will it be challeg YES
Will you get difficulty in understanding things YES (if you are a bner)
But that is what my course is for , it will help you make an app in quick 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