Publications by Chhiring Lama
Sentiment Analysis on Sexual Health
Introduction This analysis involved the collection of data from two sources: the New York Times API and an additional dataset from Kaggle. Following data collection, preprocessing and cleaning steps were performed to ensure the data’s suitability for analysis. Subsequently, sentiment analysis was conducted on the articles, comparing the frequ...
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Project_4
Introduction In this project, I aim to develop a machine learning model to classify emails as either spam or legitimate (ham). I utilize a dataset containing examples of both types of emails, where I preprocess by cleaning and converting into a suitable format for analysis. Leveraging the Naive Bayes classifier, I train the model on a portion o...
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Data in Context
2024-04-03 knitr::opts_chunk$set(echo = FALSE) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union ## Warning: package 'randomForest' was built under R version 4.3.3 ## randomFo...
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Recommendation System Discussion
Introduction: Netflix is a leading streaming service that provides a vast array of entertainment options to users worldwide. With its personalized recommendation system based on machine learning algorithms, Netflix aims to offer high-quality content tailored to individual preferences. Scenario Design: Target Users: Netflix’s audience comprise...
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Recommendation System
Implementing Global Baseline Estimate Recommender System in R Load Libraries #library(tidyverse) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(DBI)...
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Assignment10
Load libraries library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(tidyverse) ## Warning: package 'lubridate' was built under R version 4.3.2 ## ── Att...
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Web data scrapping using API key
Introduction This R document will demonstrate how to utilize the Web APIs to scrap the data from different websites. I am using The New York Times API to extract the information about top selling books. library(httr) library(jsonlite) library(request) ## Warning: package 'request' was built under R version 4.3.3 library(dplyr) ## ## Attaching...
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Web data scrapping
Introduction This R document will demonstrate how to utilize the Web APIs to scrap the data from different websites. I am using The New York Times API to extract the information about top selling books. library(httr) library(jsonlite) library(request) ## Warning: package 'request' was built under R version 4.3.3 library(dplyr) ## ## Attaching...
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Assignment7
Books Info in 3 different file formats Load libraries library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(tidyr) library(xml2) ## Warning: package 'xml2' ...
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Project 2
Dataset 1 - Purchases log data #Introduction The dataset contains transactional information from purchases made across various cities in the USA, spanning the period from January to December 2012. My focus is specifically on analyzing purchase trends during January and December, periods that coincide with the start of a new school session and t...
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