--- title: "Azmat Khan (@azm999) | Hashnode" description: "Open source enthusiast, Problem solver. Read the latest articles by Azmat Khan on Hashnode." url: "https://hashnode.com/@azm999" --- @azm999 # Azmat Khan @azm999 · india · Joined May 2023 Open source enthusiast, Problem solver ### [GSOC'23: Final Report](https://azm999.hashnode.dev/gsoc23-final-report?utm_source=hashnode&utm_medium=feed) Project Details Title: Addition of regression GAM and kNN classification functionality in statistics package Organization(s): GNU Octave, Google Summer of Code Mentors: Andreas Bertsatos and Nick Jankowski Community Discussion thread : \[ Discourse Th... 4 min read · [azm999.hashnode.dev](https://azm999.hashnode.dev/gsoc23-final-report?utm_source=hashnode&utm_medium=feed) [Aug 27, 2023](https://hashnode.com/posts/gsoc23-final-report/64eb4feccec95dea326bead7) ### [GSOC'23 Week 9 & 10: Implementing Classdef for GAM and comparision with other softwares](https://azm999.hashnode.dev/gsoc23-week-9-10-implementing-classdef-for-gam-and-comparision-with-other-softwares?utm_source=hashnode&utm_medium=feed) Classdef in Octave For Matlab compatibility and better representation of GAM model we will need a classdef RegressionGAM for storing the training data and other model parameters. The classdef here would serve as a Representation of the Training data,... 5 min read · [azm999.hashnode.dev](https://azm999.hashnode.dev/gsoc23-week-9-10-implementing-classdef-for-gam-and-comparision-with-other-softwares?utm_source=hashnode&utm_medium=feed) [Aug 26, 2023](https://hashnode.com/posts/gsoc23-week-9-10-implementing-classdef-for-gam-and-comparision-with-other-softwares/64ea489ab8fd8c72ef173f56) ### [GSOC'23 Week 8: GAM Regression Part 2](https://azm999.hashnode.dev/gsoc23-week-8-gam-regression-part-2?utm_source=hashnode&utm_medium=feed) Predicting Values from fitted model Untill Now we have Fitted the Models for Two different functions for 100 synthetic sample values with added noise. $$f\_1(x) = sin (3x).$$ and $$f\_2(x) = x^3$$ Now when the backfitting algorithm converges, the last ... 1 min read · [azm999.hashnode.dev](https://azm999.hashnode.dev/gsoc23-week-8-gam-regression-part-2?utm_source=hashnode&utm_medium=feed) [Jul 31, 2023](https://hashnode.com/posts/gsoc23-week-8-gam-regression-part-2/64ea02ada82ef43bfeb920da) ### [GSOC'23 Week 6&7: GAM Regression Part 1](https://azm999.hashnode.dev/gsoc23-week-67-gam-regression-part-1?utm_source=hashnode&utm_medium=feed) why GAMs ? A Linear Model is Represented as : $$Y=Xβ+ε$$where Y is the Response Variable, X is the predictor data, Beta is the regression Coefficient, and epsilon is the error term. Linear models are known to be all-in-one models when it comes to dat... 4 min read · [azm999.hashnode.dev](https://azm999.hashnode.dev/gsoc23-week-67-gam-regression-part-1?utm_source=hashnode&utm_medium=feed) [Jul 24, 2023](https://hashnode.com/posts/gsoc23-week-67-gam-regression-part-1/64e9fc2686052a2ea5505f88) ### [GSoC'23 Week 4: Implementing kNN algorithm for classification](https://azm999.hashnode.dev/gsoc23-week-4-implementing-knn-algorithm-for-classification?utm_source=hashnode&utm_medium=feed) kNN Algorithm in the parametric approach, we assume an underlying relationship between the predictor (input) and response (output) values. $$Y = f(X, \\theta) + \\epsilon$$Y represents the response variable, X represents the predictor variable(s), f re... 6 min read · [azm999.hashnode.dev](https://azm999.hashnode.dev/gsoc23-week-4-implementing-knn-algorithm-for-classification?utm_source=hashnode&utm_medium=feed) [Jul 3, 2023](https://hashnode.com/posts/gsoc23-week-4-implementing-knn-algorithm-for-classification/64ac0c70b2d5b84d133b4ad6)