Single header compile-time dimensional analysis for C++

This project uses machine learning to predict whether a loan applicant will repay their loan. The project uses a dataset of historical loan data from PeerLoanKart, a peer-to-peer lending platform.

This library provides a canvass-like Svelte component that encourages a deeper understanding of units. This "unit playground" aims to aid problem solvers by providing instant unit feedback, hints, and rearrangeable equations.

A type-safe representation of units with zero-run-time overhead. This library decouples the physical dimensions from the units themselves there by allowing to inter-convert between different systems such as SI and Imperial. The system allows for non-integer rational powers of physical dimensions as well(eg: L^2.5)

It has the comparison study on dimension reduction techniques PCA and t-SNE on MNIST Digit Recognitaion Dataset

C++ library of physical quantities, physical models, and units of measure for scientific computing.

My first steps to becoming AI engineer :)

This repository consists of performing Principal Component Analysis (Finding out the principle components of our dataset), using the concept of Eigen Vectors and Eigen Values of the correlation matrix. Also, it also includes the technique of reducing the dimension of the data using Singular Value Decomposition technique and reduce it to the lowe…

This project uses machine learning to predict whether a loan applicant will repay their loan. The project uses a dataset of historical loan data from PeerLoanKart, a peer-to-peer lending platform.

Java library for measures, units, and dimensions.

Desigining Advanced Data Architectures for Business Intelligence.

Header-only scalar/vector dimensional analysis library for C++11

Obtuse, but accurate, conversions [@obtuse_units]

Analyzes the units of a provided input to compile a linear combination of the specified variables to calculate an output.

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Dimensional Analysis with extensible types and mathematical operations

Dimensionality reduction is basically a process of reducing the amount of random features,attributes variables or in this case called dimensions in a dataset and leaving as much variation in the dataset as possible by obtaining a set of only relevant features to increase the effiency of a model.

A minimalist library for pivoting data by 1-n dimensions

Statically-checked physical units with seamless syntax

Dimensional analysis add-on for MS Excel