kshitizrohilla Goto Github PK
Name: Kshitiz Rohilla
Type: User
Blog: kshitizrohilla.bio.link
Name: Kshitiz Rohilla
Type: User
Blog: kshitizrohilla.bio.link
This project explores the relationship between age and height using polynomial regression. The data used in this project is given in the CSV file named age-height-data.csv.
This simple blog application provides a user-friendly platform for bloggers to publish their posts online. It is built using PHP on the server-side and uses MySQL for storing blog posts. The application allows bloggers to write blog posts, add images and publish them on the blog.
This notebook studies the time-series data of Covid-19 India data set with the following heads: date, time, state/union territory, confirmed Indian national, confirmed Foreign national, cured, deaths and confirmed(sum of confirmed Indian national and confirmed foreign national cases recorded). The data is available as a csv file.
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This project aims to predict the price of a house based on its area using simple linear regression. The dataset used in this project consists of 1000 houses in Monroe Township, New Jersey, and their respective areas and prices. The data is stored in a CSV file named house-prices.csv.
The problem involves using logistic regression to predict whether a person will purchase life insurance or not, based on their age. Since there are only two possible outcomes (i.e. purchase or not purchase), it is considered a binary logistic regression problem.
This project uses the K-Nearest Neighbors (KNN) algorithm to classify Iris flowers based on their sepal and petal measurements. The dataset used in this project is the Iris Dataset, which includes 150 samples of Iris flowers, each with four features: sepal length, sepal width, petal length, and petal width.
This is a simple JavaScript code snippet that provides real-time password validation based on specific requirements.
This is a sample project that demonstrates how to use linear regression to analyze the relationship between head size and brain weight. The dataset used in this project includes the head size (in cubic centimeters) and brain weight (in grams) of 237 adult individuals.
A simple LogIn and SignUp system made using PHP on the server side and MySQL for storing client's database consisting of their username, email and passoword using password_hash() function using a strong one-way hashing algorithm.
This project aims to perform customer segmentation on a Mall customer dataset using the K-Means clustering algorithm. The goal of this project is to cluster the customers based on their purchasing behavior and demographic characteristics.
The most customizable typing website with a minimalistic design and a ton of features. Test yourself in various modes, track your progress and improve your speed.
This project aims to predict the per capita income of Canada for a given year, based on the country's adjusted net per capita income. Specifically, the project will use historical data on Canada's income levels to develop a predictive model that can estimate the per capita income of a given year, such as 2020 or 2022.
This notebook aims to predict salaries based on years of experience using linear regression. The prediction is done from scratch without the use of external libraries such as the Scikit-learn library.
This project is a simple spell checker program written in Python. It allows you to check the spelling of words in a given text and provides suggestions for corrections if a word is misspelled.
This project aims to predict the survival of passengers aboard the Titanic using the Naive Bayes classifier algorithm. The dataset used in this project contains information about Titanic passengers, such as their age, gender, passenger class, and other relevant features.
A simple to-do list web app made using vanilla JavaScript. Users can create a list of tasks, mark them as complete, and delete them.
This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification. The goal is to train an SVM classifier to predict whether a user will purchase a particular product or not.
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