Euclidean Manhattan and Cosine Distance | Euclidean distance vs Cosine similarity

Euclidean Manhattan and Cosine Distance | Euclidean distance vs Cosine similarity
#EuclideanVsCosineSimilarity #UnfodDataScience
Hello ,
My name is Aman and I am a Data Scientist.
About this video:
In this video, I explain concepts of various distance metrics in Data Science. I explain what is Euclidean distance and what is Manhattan distance. I also explain cosine similarity with example. Below topics are discussed in this video:
1.euclidean distance vs manhattan distance vs minkowski distance
2.euclidean vs manhattan distance for clustering
3.advantages of manhattan distance
4.knn manhattan distance
5.hamming distance vs euclidean distance
6.bray curtis vs euclidean distance
7.properties of manhattan distance
8.tf manhattan distance
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
If you need Data Science training from scratch . Please fill this form (Please Note: Training is chargeable)
docs.google.com/forms/d/1Acua...
Book recommendation for Data Science:
Category 1 - Must Read For Every Data Scientist:
The Elements of Statistical Learning by Trevor Hastie - amzn.to/37wMo9H
Python Data Science Handbook - amzn.to/31UCScm
Business Statistics By Ken Black - amzn.to/2LObAA5
Hands-On Machine Learning with Scikit Learn, Keras, and TensorFlow by Aurelien Geron - amzn.to/3gV8sO9
Ctaegory 2 - Overall Data Science:
The Art of Data Science By Roger D. Peng - amzn.to/2KD75aD
Predictive Analytics By By Eric Siegel - amzn.to/3nsQftV
Data Science for Business By Foster Provost - amzn.to/3ajN8QZ
Category 3 - Statistics and Mathematics:
Naked Statistics By Charles Wheelan - amzn.to/3gXLdmp
Practical Statistics for Data Scientist By Peter Bruce - amzn.to/37wL9Y5
Category 4 - Machine Learning:
Introduction to machine learning by Andreas C Muller - amzn.to/3oZ3X7T
The Hundred Page Machine Learning Book by Andriy Burkov - amzn.to/3pdqCxJ
Category 5 - Programming:
The Pragmatic Programmer by David Thomas - amzn.to/2WqWXVj
Clean Code by Robert C. Martin - amzn.to/3oYOdlt
My Studio Setup:
My Camera : amzn.to/3mwXI9I
My Mic : amzn.to/34phfD0
My Tripod : amzn.to/3r4HeJA
My Ring Light : amzn.to/3gZz00F
Join Facebook group :
groups/41022...
Follow on medium : / amanrai77
Follow on quora: www.quora.com/profile/Aman-Ku...
Follow on twitter : @unfoldds
Get connected on LinkedIn : / aman-kumar-b4881440
Follow on Instagram : unfolddatascience
Watch Introduction to Data Science full playlist here : • Data Science In 15 Min...
Watch python for data science playlist here:
• Python Basics For Data...
Watch statistics and mathematics playlist here :
• Measures of Central Te...
Watch End to End Implementation of a simple machine learning model in Python here:
• How Does Machine Learn...
Learn Ensemble Model, Bagging and Boosting here:
• Introduction to Ensemb...
Build Career in Data Science Playlist:
• Channel updates - Unfo...
Artificial Neural Network and Deep Learning Playlist:
• Intuition behind neura...
Natural langugae Processing playlist:
• Natural Language Proce...
Understanding and building recommendation system:
• Recommendation System ...
Access all my codes here:
drive.google.com/drive/folder...
Have a different question for me? Ask me here : docs.google.com/forms/d/1ccgl...
My Music: www.bensound.com/royalty-free...

[@yogalakshmiramesh8895]

Lovely explanation. Awesome!!!! thanks a lot

[@anilshinde8025]

Great. Nice explaination

[@swethanandyala]

if it is Amans video first like and then watch!!!.... thank you for sharing your knowledge

[@UnfoldDataScience]

Thanks Swetha, means a lot

[@soheilaahmadi4807]

amazing like always. Thank you so much

[@sandeepchandra5033]

Very good Explanation sir.
We need more videos like this...!!!.
Thanks for your efforts & sharing knowledge 🙏
Note:- could you please explain if we 2 data sets csv files like train csv file 1459 rows and 81 columns and 1460 rows 80 columns after merged model implementation. supervised techniques and finally want ID column and salaried to csv how do work could please explain sir

[@UnfoldDataScience]

Thanks, will check your problem.

[@ANSHULJAINist]

Amazing explanation.

[@santoshr1708]

Thank you sir. This was really helpful. I have a request. Please a detailed video on Iris dataset using k - means clustering. It will help me as well as everyone a lot. I didn't find any good video on Iris dataset. So, it would be great if you make one on this.

[@UnfoldDataScience]

K means videos are already there, please see this complete playlist
ruclips.net/video/LCpihhKcJQs/видео.html

[@santoshr1708]

@@UnfoldDataScience Watched the video but I was saying to make a project video on iris dataset.

[@shubhamchoudhary5461]

Very good Explanation sir.
We need more videos like this...!!!.
Thanks for your efforts & sharing knowledge 🙏

[@UnfoldDataScience]

So nice of you Shubham.

[@RamanKumar-ss2ro]

Thanks for the video.

[@UnfoldDataScience]

Thanks a lot.

[@suleymanerim2119]

Thanks, good clarificiation

[@UnfoldDataScience]

Glad it was helpful!

[@prabhakarm5819]

simply & easy way understading all your concepts.Can you createNLP playlist also. So useful.Your way of teaching i feel so light. Super.

[@UnfoldDataScience]

Thanks a lot Prabhakar. Please find NLP playlist here:
ruclips.net/video/cs049uQWbpg/видео.html

[@IRFANSAMS]

Your videos are super awesome for some one who is doing self study on ML

[@UnfoldDataScience]

Thanks alot, please share with others too.

[@dhlpaket2247]

You are amazing
Thank you

[@UnfoldDataScience]

Welcome.

[@61_shivangbhardwaj46]

Sir you r best
How easy explanation it is!
Thnx sir😊

[@UnfoldDataScience]

Thanks a lot.

[@pramodyadav4422]

Every video is clearing the doubt.

[@UnfoldDataScience]

Thanks again Pramod. Your comments mean a lot.

[@pramodyadav4422]

@@UnfoldDataScience do you have any plan to teach online someone ? Like mini batch type ??

[@rishigupta2342]

Good explanation!!!

[@UnfoldDataScience]

Thanks

[@sandipansarkar9211]

finished watching

[@RanjitSingh-rq1qx]

Sir, you are to good. I had many doubts in my mind before watching this video. But now not anyone ☺️. And one more thing sir please arrange the white board little bigger 😊🥰😍

[@UnfoldDataScience]

Thanks Ranjit . Yes new digital board is in use now

[@radhakrishnanananthan1585]

Nice Video Aman Sir. Can you please share videos on SVD and PCA.

[@UnfoldDataScience]

As soon as possible. Thanks for suggestion.

[@ajaykushwaha-je6mw]

Requesting you to kindly show the same using Python code.

[@UnfoldDataScience]

Will Do Ajay.

[@balapranav5364]

Grower distance please

[@UnfoldDataScience]

Sure.

[@nikhilgupta4859]

Not impressed sir with this video, this video is nothing more than hundreds of videos available online.
We see your videos for something extra.
People are searching for the case where we decide which distance should be used based on data.

[@UnfoldDataScience]

Thanks Nikhil for the feedback. I will take care of it. Stay safe. tc

[@sandipansarkar9211]

finished watching