An exploratory analysis of the Kaggle bikeshare data set with the application of linear regression models, which are not optimal for this particular problem of predicting bikes rented.
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Updated
Dec 11, 2018 - R
An exploratory analysis of the Kaggle bikeshare data set with the application of linear regression models, which are not optimal for this particular problem of predicting bikes rented.
Logistic optimization: Delivery drivers location optimization with Causal Inference
Portfolio of personal projects & curriculum from Springboard
Performed statistical analysis and modelling to estimate the relationship between the price of diamonds and other variables related diamond features from a diamond dataset.
Landing page for the SMiG Lab
The model in this paper analyses and optimizes the evaluation system, provides perfect data support to improve customers' experience of watching network video, and can successfully solve the problems of system optimization and customer support .
Explore glider aviation safety through in-depth data analysis. This project leverages incident reports and manufacturing data, utilizing Python and Jupyter Notebooks for trend identification, risk assessment, and safety enhancement in glider aviation.
In this project, I web scraped and parsed listing available high-rated apartments within 2 miles around Boston Univeristy Center from apartments.com, analyzed price, vacancy, special promotions against different room types, and discovered the price and availability trends in 2021.
These are the projects and assignments done by me to practice and work on improving my skills and knowledge.
This repository contains some of the lab exercises carried out using R for the course Statistical Modeling 1 at Tampere University
Depression & Genetic Variables: Analyzing Associations
A series of Statistical Modelling assignments with the use of R. Applications of Linear, Polynomial, Logistic and Poisson Regression in various datasets
RStudio project utilizing various statistical methods to replicate and diagnose the findings of Appel and Loyle from their study on post-conflict justice and foreign direct investment.
Tool for extracting part of speech n-grams (POS-grams) together with their context (preceding/following POS or sentence onset/ending).)
Exploring and Predicting California's housing data
Predicting loan interest rate using R.
A project utilizing NLP techniques and analysis including text mining, document term matrices, sentiment analysis, wordclouds and topic modeling with LDA.
📊⚙️ Using 7 years of my sleep data, this project predicts Sleep Quality using a linear regression model based on predictors such as time in bed, time asleep, temperature, alarm, and steps.
Augmented backward elimination for SAS: A Pragmatic and Purposeful Way to Develop Statistical Models
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