Library for processing and extracting assets for the 3D/ADV engine
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Updated
Jun 23, 2024 - JavaScript
Library for processing and extracting assets for the 3D/ADV engine
Learning mathematical methods of data analysis in the language R.
A series of Jupyter notebooks, to know about Machine Learning, its implementation, and identifying its best practices.
Gaussian Navie Bayes Classifier was applied on IRIS dataset. Different types of normality tests were used to introduce the normality concepts.
Determined the best regression model which represents the data
All my R code used for statistical analyses - Hypothesis Testing, t-tests, etc.
Kernels for machine learning problems
Testing effects of missing data on phylogenetic inferences
This a project I did in the Spring of 2017 for the graduate course of Statistical Computing. This project includes T-Tests, Non-parametric Tests, Linear Regressions, Correlation Tests, Chi Square Tests, and tests for normality. This project also includes some basic graphing.
This is a homework I did in the Spring 2017. It involves conducting Chi Square Tests, Confidence Intervals, Kolmogorov-Smirnov Tests, and Shapiro-Wilk Normality Tests. It has problem numbers that are associated to problems in "Using R: Introductory Statistics".
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