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activity-05-mini-competition

activity01-course-tools

Task 1: Forking the Repository

activity02-slr

This task is for week 3 activity 2 day 1 on Simple Linear Regression (SLR)

activity03-mlr

Multiple Linear Regression

activity04-regression-considerations

activity06-logistic-regression

Logistic Regression

activity07-discriminant-analysis

Generalized Linear Models

activity08-mini-competition

activity09-bootstrapping

creating-dashboard-and-data-visualization-project

In this project, the datasets named Claim, Demographic, Policy, Vehicle and Fraud from the datasets of Insurance Fraud have been analyzed and a dashboard was created using the Óexdashboard package showing few visualizations and summary table.

data-mining-project

The project consists of two separate tasks. In the first, my partner and I were given data about patients in medical studies and asked to find an appropriate classifier to describe the nature of the data. In the second, we were to do a similar analysis on a real data set of our own choosing. We choose Breast Cancer Wisconsin (Original) data.

deliverables-statistical-modeling-and-regression

This repository contains all the prepared assignments of STA 631 (Statistical Modeling and Regression)

early-eval

Evaluation

health-and-bioinformatics-project

In this project, we re-analyzed the genes from 26 healthy subjects and 20 hypertensive patients using GEO2R to compare the two groups (e.g., HealthySubject and HypertensionPatient) of Samples in order to identify the differentially expressed genes across experimental conditions.

information-visualization-project

Breast Cancer Wisconsin (Original) Data Set Analysis and Visualization

lged-rtip-ii-project

World Bank funded LGED RTIP-II project

machine-learning-project-1

Data Visualization and Analysis; Package used: matplotlib

machine-learning-project-2

Part-I: Naïve Bayes for Classification; Part-II: Naïve Bayes for Spam Classification; Packages used: defaultdict, corpus, math, GaussianNB, numpy, word_tokenize

machine-learning-project-3

Decision Tree Construction via ID3 Algorithm; Packages used: defaultdict, math, Queue, pandas, Network, graphviz, tree

machine-learning-project-4

Learning a Linear Function via Perceptron and Backpropagation for Neural Network Learning; Packages used: Perceptron, DataFrame, numpy, pandas, seed, random, math

research-on-renewable-energy

Improving Solar Cell Efficiencies

statistical-modeling-and-regression-analysis

Breast cancer is a major health concern among women worldwide. Early detection and accurate diagnosis can improve patient outcomes and increase the chance of successful treatment. This project aims to use logistic regression to predict breast cancer diagnosis based on the Wisconsin Breast Cancer dataset.