Notebook image and notebook for feature reduction talk
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Updated
Jun 5, 2017 - Jupyter Notebook
Notebook image and notebook for feature reduction talk
Used to perform Ant Colony optimisation with Linear Discriminant Analysis for feature reduction in a dataset.
Application of principal component analysis (PCA) for feature reduction.
Interactive dashboard in R using JavaScript based libraries (flexdashboard, highcharter, etc.) showing US university statistics. Data sourced from catalog.data.gov for year 1996 to 2017. Size 2.5 GB/1900+ columns.
A data science technique implemented in OpenCL.
A binary image classification problem
Presenting a method based on machine learning to predict Parkinson's disease using audio signals
AS-DMF framework guide
Exploring taxonomical/morphological uses for Rhododendron images
An apple classification binary problem
A Python implementation of RSLDA (paper "Robust Sparse Linear Discriminant Analysis").
Implementation of a Peak detection pipeline in Python using machine learning models and sliding window on the H3K9me3_TDH_BP ChIP-seq dataset.
Feature reduction of multivariate time series data for fault localization in Python
Cross the PPI products to those customers who currently don't have one.
This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: COVID-19 positive, pneumonia positive, and normal. To achieve this, we utilize the COVID-19 Chest X-ray dataset available on Kaggle.
📊 Computation and processing of models' parameters
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