poshan0126

Poshan Pandey's repositories

COVID-19-dataset-and-World-Happiness-Report-Analysis

I performed Data Analysis on COVID 19 dataset by John Hopkins University and World Happiness Report and found really interesting results. It shows that people living in developed countries are more prone to infection of the Corona Virus than people living in less developed countries.

Language:HTML1 20

Epoch-Programmers-CodeBase

This repository consists of all the codefile that is taught in the youtube channel Epoch Programmers

Language:Dart1 20

NCIT-Note-Finder

Djangoish Web App that gives Students of NCIT and/or Pokhara University to download notes with a click of a button.

Language:JavaScriptMPL-2.01 10

poshan0126

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SentiMeter_Proposal_Documents

This repo consist of the documents that we made during our college project Sentimeter.

1 20

SentiMeter_Twitter_Sentiment_Analysis

This repository consist of a small terminal application that analyzes tweets of user given keyword and number and provides the result on their sentiment.

Language:Python1 20

E-Commerce-API---Flask

This project is a mini e-commerce API built using Flask and SQLAlchemy.

Language:Python000

100algorithms

Language:TypeScript010

4TH-NATIONAL-WORKSHOP-ON-MACHINE-LEARNING-DATA-SCIENCE-Project-1-

Language:Python000

Awesome-Profile-README-templates

A collection of awesome readme templates to display on your profile

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awesome-README-templates

A collection of awesome readme templates to display on your github profile.

Language:JavaScriptMIT010

bellini

Bayesian Learning on Laboratory Investigation

MIT000

bubble

Speech bubble for Flutter

BSD-2-Clause000

class-ultimate-classof2020

Ultimate Repo For The Class Section Of ClassOf2020. Live ==

Language:JavaScriptMIT010

Classroom-Attendance-System-Utilizing-Viola-Jones-for-Face-Detection-and-LBPH-for-Face-Recognition

The face of a human is crucial for conveying identity. Computer scientists, Neuro scientists, and psychologists, all exploits this human feature using image processing techniques for commercial, and law enforcement applications. Likewise, this feature can be invited into classrooms to maintain records of students’ attendance. Con- temporary traditional way of recording attendance involves human intervention and requires cooperation of the students which is hectic and contribute towards waste of class time. An automated real-time classroom attendance system detects students from still image or video frame coming from a digital camera, and marks his/her attendance by recognizing them. The system utilizes Viola–Jones object detection framework which is capable of processing images extremely rapidly with high detec- tion rates. In the next stage, the detected face in the image is recognized using Local Binary Patterns Histogram.

Language:Python010