Apply modern, deep learning techniques for anomaly detection to identify network intrusions.

Application of Deep Learning and Feature Extraction in Software Defect Prediction

Repo to analyze population genetic data with many different methods

This Repository Contains R-Codes executed on various Datasets in RStudio. I Hope This Repository is very helpful for those who are Willing to build their Career in Data Science, Big Data.

ROS package for creating a terrain cost map using RGBD Camera for locomotion of legged Robots.

A cross compiled Scala.js port of JAMA for JVM, JavaScript, and Scala Native projects.

PCA(Principle Component Analysis) For Seed Dataset in Machine Learning

Machine learning problem sets from Stanford University's Machine Learning course on Coursera

Machine learning with MATLAB/Octave, coding machine learning algorithms from scratch

Heart disease detection using different classifiers and neural network with feature engineering.

Toolkit for Data Science & Statistics

An binary classification model based on principle component analysis and fuzzy inference system. It takes brain MRI images and predicts whether the MRI image contains a tumor or not.

RGB data processing pipeline including auto-white-balance based on principle component analysis (PCA).

This is a 16S amplicon analysis for visualizing microbiome data using QIIME, QIIME2R and Phyloseq. DNA was isolated fom both sediment cores and seabird fecal samples for this analysis.

Python version of exercises in the Coursera course of Machine Learning provided by Stanford University (https://www.coursera.org/learn/machine-learning)

An in-depth comparison of two prominent intrusion detection datasets: KDDCup99 and NSL-KDD

Principle Component Analysis Clustering Visualization for Iris dataset

Principle Component Analysis

Contains code and detailed write ups created while taking a class on Data Driven Modeling & Scientific Computation with Professor Nathan Kutz.

Prediction and classification of breast cancer using standard scaling, PCA, and SVM.