Bhargav Venkat

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Grade 10 | Points: 56445 | Rank: 1

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Classes completed

255

Quizzes submitted

243

Projects submitted

252

Hackathons

Code Clash Championship | Hackathon Competition for Kids and Teens

Hosted by: IIT Kanpur Antargani

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Code Clash Championship | Hackathon Competition for Kids and Teens

Hosted by: IIT Kanpur Antargani

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HackYoung Olympiad 2024

Hosted by: Codingal

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CodeGenius Hackathon

Hosted by: Codingal

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CodeGenius Hackathon

Hosted by: Codingal

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HPE CodeWars 2024 Hackathon

Hosted by: Hewlett Packard Enterprise

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Coding contests

IOI Algorithms Preparation Guide

Hosted by: Codingal

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HPE CodeWars 2023 Code Battle

Hosted by: Hewlett Packard Enterprise

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Codewars All Practice Problems 2023

Hosted by: Codingal

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CodeWars 2021 - All past problems

Hosted by: Codingal

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Cypher

Hosted by: Seth Anandram Jaipuria School Ghaziabad

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Coding Challenge Practice Arena

Hosted by: Codingal

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Activities

Apply the multi-class regression algorithm to the given dataset

Write a program to check whether the dataset can be used as a multi-class classification and its algorithm.

Apply the binary class algorithm to the given dataset

Write a program to check whether the dataset can be used as binary classification and its algorithm.

Logistic Regression analysis

Write a program to create a logistic regression model and predict the values.

Logistic Regression analysis

Write a program to check whether the dataset is binary or multi-class classification and use logistic regression to analyse it.

Maximum Margin separating hyperlink.

Write a program to create a margin between the data points to separate.

Identify the dataset for the classification.

Write a program to check whether the dataset can be used as binary classification or multi-class classification.

Projects

Multi-class Classification.

Students have to make a machine learning model for predicting the target feature from the given set of features in the array.

Binary class Classification.

Students have to make a machine learning model for predicting the values of “x” using the values of “y” in the given data set using the binary class classification process.

Logistic Regression.

Students have to make a machine learning model for predicting the values of “x” using the values of “y” in the given array using Logistic Regression analysis.

Data Classification.

Students have to perform the steps of classification to check whether the dataset is binary or multi-class.

Full Implementation of regression analysis

Students have to implement the regression analysis model using gradient descent and plot the graph accordingly.

Data Classification.

Students have to create a classification set after preprocessing the dataset given.