K-Nearest Neighbor Classification (K-NN) Using Scikit-learn in Python – Tutorial 25




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In this tutorial, you will learn, how to do Instance based learning and K-Nearest Neighbor Classification using Scikit-learn and pandas in python using jupyter notebook. K-Nearest Neighbor Classification is a supervised classification method.

This is the 25th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist “the sexiest job of the 21st century.” Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We’ll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets.

Download Link for Cars Data Set:
https://www.4shared.com/s/fWRwKoPDaei

Download Link for Enrollment Forecast:
https://www.4shared.com/s/fz7QqHUivca

Download Link for Iris Data Set:
https://www.4shared.com/s/f2LIihSMUei
https://www.4shared.com/s/fpnGCDSl0ei

Download Link for Snow Inventory:
https://www.4shared.com/s/fjUlUogqqei

Download Link for Super Store Sales:
https://www.4shared.com/s/f58VakVuFca

Download Link for States:
https://www.4shared.com/s/fvepo3gOAei

Download Link for Spam-base Data Base:
https://www.4shared.com/s/fq6ImfShUca

Download Link for Parsed Data:
https://www.4shared.com/s/fFVxFjzm_ca

Download Link for HTML File:
https://www.4shared.com/s/ftPVgKp2Lca

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Comment List

  • TheEngineeringWorld
    November 21, 2020

    **DO NOT CLICK DOWNLOAD ON THE 4SHARE LINKS ON THE DESCRIPTION. I TRIED THE "CARS" ONE AND IT DOWNLOADED A TROJAN VIRUS ON MY WORK COMPUTER. IT PROMPTED A POP-UP AND AUDIO STATING TO CALL THE SUPPORT NUMBER ON SCREEN. I MANAGED TO CLOSE IT AND NOW I'M RUNNING A FULL SYMANTEC SCAN. YOU ARE ALL FOREWARNED**

  • TheEngineeringWorld
    November 21, 2020

    Amazing amazing very useful and well made tutorial, thank you sir!

  • TheEngineeringWorld
    November 21, 2020

    Hi sir, can you please make a video about Image segmentation with KNN in python from scratch please, it would help me a lot with a project

  • TheEngineeringWorld
    November 21, 2020

    You can improve this by explaining more about hyper parameters and about tweaking the model according to the problem

  • TheEngineeringWorld
    November 21, 2020

    No module named 'sklearn.cross_validation'

  • TheEngineeringWorld
    November 21, 2020

    can I get the code please?

  • TheEngineeringWorld
    November 21, 2020

    ( Download Link for Cars Data Set: ) this link is not working properly. will you please provide us the data set ( for all data set) via another medium. … Thanks in advance 🙂

  • TheEngineeringWorld
    November 21, 2020

    content is good but allow way to many advertisement.. which makes it annoying

  • TheEngineeringWorld
    November 21, 2020

    how plot the dataset in clusters?

  • TheEngineeringWorld
    November 21, 2020

    Can you please share this dataset and code?

  • TheEngineeringWorld
    November 21, 2020

    @TheEngineeringWorld – excellent video here on K-Nearest Neighbors concepts and application code. Your data science videos are excellent for developing to an intermediate and advanced level of data science skills, working from a foundation that one already has an introductory level skill set. I am sure your approach builds your own professional standing in the data science community, as well as enhancing our skill set in the field. Many thanks.

  • TheEngineeringWorld
    November 21, 2020

    how to import reParams from sklearn pelase?

  • TheEngineeringWorld
    November 21, 2020

    Thank you so much for this! You saved my life

  • TheEngineeringWorld
    November 21, 2020

    Thank you for this introductory video to kNN, I would have liked to understand how the model got k=5 and how is the prediction actually returning 0 or 1 instead of outputting the number of nearest neighbors it found. Finally, you mentioned that this approach is only good for small datasets can you elaborate why also any ideas on what to use for large datasets instead of knn?

  • TheEngineeringWorld
    November 21, 2020

    Thanks for the tutorial!

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