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Bhargav Venkat

Grade 10 | Points: 60965 | Rank: 1

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Classes completed

271

Quizzes submitted

259

Projects submitted

268

Hackathons

IIT Kanpur Antargani

Code Clash Championship | Hackathon Competition for Kids and Teens

Hosted by: IIT Kanpur Antargani

IIT Kanpur Antargani

Code Clash Championship | Hackathon Competition for Kids and Teens

Hosted by: IIT Kanpur Antargani

Codingal

HackYoung Olympiad 2024

Hosted by: Codingal

Codingal

CodeGenius Hackathon

Hosted by: Codingal

Codingal

CodeGenius Hackathon

Hosted by: Codingal

Hewlett Packard Enterprise

HPE CodeWars 2024 Hackathon

Hosted by: Hewlett Packard Enterprise

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Coding contests

Codingal

IOI Algorithms Preparation Guide

Hosted by: Codingal

Hewlett Packard Enterprise

HPE CodeWars 2023 Code Battle

Hosted by: Hewlett Packard Enterprise

Codingal

Codewars All Practice Problems 2023

Hosted by: Codingal

Codingal

CodeWars 2021 - All past problems

Hosted by: Codingal

Seth Anandram Jaipuria School Ghaziabad

Cypher

Hosted by: Seth Anandram Jaipuria School Ghaziabad

Codingal

Coding Challenge Practice Arena

Hosted by: Codingal

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Activities

Try Different Layers

Open the link to the page given below. Consider you have been given a dataset - Pima Indians onset of diabetes dataset. It describes patient medical record data for Pima Indians and whether they had an onset of diabetes within five years. As such, it is a binary classification problem (onset of diabetes as one or not as 0). This dataset consists of a total of 3 features/columns, including diabetes onset. Now, set the training to testing ratio to 80%. Now try adding hidden layers and neurons in each hidden layer and create a google document to enter values of testing loss for the following entries - 1) 1 Hidden layer (3 neurons) 2) 2 Hidden layers (3 neurons) 3) 3 Hidden layers (3 neurons) 4) 4 Hidden layers (3 neurons) 5) 3 Hidden layers with eight neurons 6) 3 Hidden layers with six neurons

My Neural Network

Open the notebook attached to this activity, and based on the given image and problem, answer the questions regarding the neural network that you can create. Submit this updated notebook link in the submission section.

AI around me!

Mention the products of AI around you in different domains. Let’s see how many you can guess? Make a copy of this file and then edit it to submit your answers.

Things Translator

Take a picture of something to hear how to say it in a different language. This experiment uses Artificial Intelligence to detect an image and say it in multiple languages.

Quick Draw

Play this game to understand how AI can recognize the word through doodles drawn by the player. In Quick Draw, a model has been created which has been trained on multiple images of different objects, and it gets trained through doodles drawn by players as well. And this is how AI is making this game smarter every time.

K-Means with Elbow Method

Apply the K-Means Clustering Algorithm on the Live dataset, which contains the user reaction information on the items. Do this activity by applying the elbow method to find the optimal number of clusters.

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Projects

Applications of Artificial Intelligence

Students have to create a detailed document about any two applications of Artificial Intelligence. It may include any example - Google Translator, Alexa, Self Drive Cars, or Sofia the robot.

K-Means clustering on live selling dataset

Students must implement the K-Means clustering algorithm to the Live selling dataset. Then, try to find out the accuracies by using the different numbers of clusters.

Applications of Unsupervised Learning

Students have to explain in brief the Applications of Unsupervised Learning Algorithms. You can use appropriate images for your ideas and explanations.

Apriori Algorithm on Grocery Store dataset

Students must implement the Apriori Association algorithm to the grocery store dataset and find out the association rule.

DBSCAN clustering analysis

Students must implement the DSCAN clustering algorithm on the customer dataset and make the unique clusters and visualize them.

K-Means clustering for college data

Students must implement the K-Means clustering algorithm on the college dataset and make the clusters based on private and public colleges.

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