K - Nearest Neighbors

K Nearest Neighbour is a simple algorithm that stores all the available cases and classifies the new data or case based on a similarity measure. It is mostly used to classifies a data point based on how its neighbors are classified. In this, we workshop we will learn another and very popular Classification ML Model.

Oct 10, 2020, 3:00 – 4:15 PM

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Key Themes

Machine Learning

About this event

Workshop 10 | Machine Learning: Zero to Hero

In pattern recognition, the k-nearest neighbor algorithm is a non-parametric method proposed by Thomas Cover used for classification and regression. In both cases, the input consists of the k closest training examples in the feature space. In this, we workshop we will learn another and very popular Classification ML Model.

When

When

Saturday, October 10, 2020
3:00 PM – 4:15 PM UTC

Agenda

Introduction to K - NN
Python Implementation
Training ML Model
Finding an Optimal K Value
Visualization
Q/A

Speaker

  • Muhammad Huzaifa Shahbaz

    Lenaar Digital

    Co-founder

Partners

Amal4Ajar logo

Amal4Ajar

IEEE Computer Society SSUET logo

IEEE Computer Society SSUET

IEEE SSUET - Student Branch logo

IEEE SSUET - Student Branch

Women in Engineering - Sir Syed University logo

Women in Engineering - Sir Syed University

Organizers

  • Laiba Rafiq

    GDSC Lead

  • Maaz Farman

    SPARK⚑BIZ

    Community Mentor

  • shayan faiz

    techrics

    Outreach Coordinator

  • Muhammad Ahmer Zubair

    Sharp Edge

    Media Creative Lead

  • Ehtisham Ul Haq

    Tech Lead

  • Mohammad Nabeel Sohail

    AI and Chatbot Developer | Full Stack Web | PAFLA Ambassador | Public Speaker | Trainer

    Communications Lead

  • Kashan Khan Ghori

    Softseek International

    Operations Lead

  • Daniyal Jamil

    Technology Links

    Marketing Lead

  • Sami Faiz Qureshi

    ConciSafe

    Event Management Lead

  • Maham Amjad

    Content Writing Lead

  • Syed Affan Hussain

    HnH Soft Tech Solutions Pvt Ltd

    Host

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