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Assessing your cultural and operational fit
Shubham619.github.io
August 12, 2025 – December 2, 2025
Shubham619.github.io — GitHub repository
View ProjectIntent-Classifier_Tensorflow_pipeline
September 20, 2019 – March 19, 2020
Intent-Classifier_Tensorflow_pipeline — GitHub repository
View ProjectWebscrapping-and-Topic-modeling
April 29, 2019 – April 29, 2019
Webscrapping-and-Topic-modeling — GitHub repository
View ProjectR-NLP-Package-work-
February 14, 2019 – February 14, 2019
R-NLP-Package-work- — GitHub repository
View ProjectMicrosoft-Malware-Detection
January 16, 2019 – September 20, 2024
Microsoft-Malware-Detection — GitHub repository
View ProjectQuora-Question-Pair-Similarity-Problem
January 16, 2019 – January 16, 2019
Quora-Question-Pair-Similarity-Problem — GitHub repository
View ProjectStackoverflow-Tag-Predictor
January 16, 2019 – September 20, 2024
Stackoverflow-Tag-Predictor — GitHub repository
View Projectcleandata
February 7, 2018 – Present
To install this package use this- devtools::install_github("Shubham619/cleandata") #Overview -remove_timestamp() :- to remove timestamp from data. -clean_first_col() :- for cleaning name column(must be your first column). -remove_bracs() :- removing brackets from column name and data between brackets. -adding_col_bind() :- creating dataframe with first two NA rows and NA column. -load_workbook_sheetname() :- loading worksheet and sheetname of it.
View ProjectEnsemble-models-using-Caret
November 14, 2017 – November 17, 2017
Ensemble technique is used for combining two or more algorithms of similar or dissimilar types.I have performed One hot-encoding before splitting data and then recursive feature selection. Different methods are used for predicting loan approval such as averaging, majority votes and weighted average. I have applied Caret ensemble method which combines several models via stacking. Applied robust classification algorithm such as Gradient boosting machine which the accuracy of our model.
View ProjectCase-Study-in-HR-analytics-Rmarkdown
October 17, 2017 – Present
Text mining project which determines how employees review both Amazon and Google. We can determine which company has Better work-life balance and a better pay according to online reviews.Used bag of words for analyzing text data and text visualization in a way that's both informative and engaging.Feature extraction and analysis using bag of words, which is a model for simplifying representation used in natural language processing.Lastly there are reproducible and dynamic reports with Rmarkdown.
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate initiative and a passion for data science, aligning with a culture that values self-driven learning and exploration. The diversity of projects (NLP, malware, HR analytics) suggests adaptability and a broad interest in applying data science to different domains. However, the lack of team-based projects or professional experience makes it difficult to fully assess collaboration and cultural integration.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.