- 👋 Hi, I’m @TheGospeler
- 👀 I’m interested in developing products using Machine Learning and statistical analysis, with the aim of hedging on the new data-driven world
- 🌱 I’m currently learning Various computational modeling techniques and building computational prowess at MSU
- 💞️ I’m looking to collaborate on products that involve Automation, Machine Learning, Remote Sensing, and the overall usage of the Artificial Intelligence processes
- 📫 You can reach me at johnsalako3@gmail.com or LinkedIn (Check Bio.)
Discover how I reduced the dimension of a dataset from 71 columns to 16 columns using basic EDA to a more robust statistical analysis using the Lasso regression Model. This led to an average accuracy of 92% using 11-fold cross-validation.
Discover how I created a web application that allows you to perform several Exploratory Data Analyses (EDA) on the Tetuoan Power Consumption Data using interactive plots and other great visualization plots in Python, such as Altair, HiPlot, and Joint Plot.
Data Science Application!
Discover how I combined four regressional algorithms in creating this machine-learning web application with a stunning interface and interactive GUI that allows a user to perform hyperparameter tuning and feature selection. Also, an introduction to the One-Step-Ahead method is presented, and the power consumption data is forecasted in the Label Prediction from label tab.
Machine Learning Application!
Root Distribution Analysis and Computational Processes (Check Root-Distribution-Analysis-and-Computation)
Discover how I combined the Ground Penetrating Radar and Several Artificial Intelligence algorithms to assess the roots of trees and present a 3D view of the tree roots.
This was a fun project to work on. Three different modules are presented here. The animation shows the success of the software in attempting to reconstruct the roots of trees using Electrical Resistivity Tomography (ERT).
