Sørensen–Dice coefficient

PyAbsorp is a python module that has the main focus to help estimate the Sound Absorption Coefficient using analytical models.

digital signal processing FIR filter implimentation in microcontroller

Quadratic Equation Solver. We can help you solve an equation of the form "ax2 + bx + c = 0" Just enter the values of a, b and c below: a. x2 +. b. x +. c. = 0.

avsdbdg_3v3 is a Bandgap Reference circuit, which is used to generate a constant voltage reference in analog domain which is independent of temperature and supply voltage variations.

This example calculates the Pearson correlation coefficient (r), by measuring the linear relationship between two arrays. The use of means and then the accumulators, shows how covariance and variance combine into (r), with results from -1 to +1. Implemented in Python, MATLAB, and JavaScript.

The Cramer, Determinant, Coefficient, Multiplication for the matrix.

Import og generate reports and analytics from a Microsoft Forms Excel export.

Compute a moving sample Pearson product-moment correlation distance incrementally.

Typical subject topics are covered, in 167 notebooks. Streamlined Mathematica shortcuts take precedence over traditional precursor methods. A number of problems are dealt with in an inept, tentative, inefficient, or erroneous manner.

Return an integer corresponding to the significand of a single-precision floating-point number.

A utility library for comparing strings via the Dice Coefficient algorithm

Webapp that uses AngularDART framework to calculate Water quality in open-channel systems.

Return an integer corresponding to the significand of a half-precision floating-point number.

In this simple project I calculate coefficient clustering of a network data.

Automate some statistics metods in Python.

An item/document distribution suggestion based on user load calculation.

This is the last project in Level 1 of roadmap, and it was not classification this time, but Linear Regression. This project enabled me to understand the residuals, and check if there were any outliers by the graph. I even learnt the different types of encoding like one-hot, ordinal encoding. I even compared with other models like random forest

Executed Regression modelling, hypothesis testing and statistical analysis to predict factors affecting credit card balances in a firm. Tools & technologies: ANOVA, p-value, R square

Function to select features for a ML model based on a coeffecient threshold (See README).