GitHub / Sarthak-Mohapatra / Building-Algorithm-from-scratch-for-prediction-of-Average-GPU-run-time-and-classifying-the-run-type.
As part of this project, I have developed algorithms from scratch using Gradient Descent method. The first algorithm developed will be used to predict the average GPU Run Time and the second algorithm will be used to classify a GPU run process as high or low time consuming process.
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PURL: pkg:github/Sarthak-Mohapatra/Building-Algorithm-from-scratch-for-prediction-of-Average-GPU-run-time-and-classifying-the-run-type.
Stars: 2
Forks: 0
Open issues: 0
License: None
Language: R
Size: 3.33 MB
Dependencies parsed at: Pending
Created at: over 5 years ago
Updated at: over 1 year ago
Pushed at: about 5 years ago
Last synced at: over 1 year ago
Topics: algorithm-from-scratch, classification, classification-algorithm, classification-model, convergence, error-curves, experimentations, exploratory-data-analysis, gpu, gradient-descent, linear-regression, logistic-regression-algorithm, machine-learning-algorithms, matrix, prediction, regression-algorithms, regression-models, rstudio, threshold, train-test-error