Supervised Machine Learning algorithms for Regression in R and Python
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Updated
May 21, 2023 - R
Supervised Machine Learning algorithms for Regression in R and Python
Implementation of the Log-linear classifier and the MLP1 classifier from Assignment 1 in ׳Deep Learning for Texts and Sequences' course using PyTorch
Simulates Chemical Reaction System of Partial-Log-Linear Model
As part of this project, we have used Regression Analysis on top of a panel data on Guns in USA to determine the "Effect of Shall-Carry Law on Violence Rate and Incarceration Rate in United States".
Business Cycle Regularities in 2 countries
Final project for PHST 684 at the University of Louisville (Categorical Data Analysis)
First assignment in ׳Deep Learning for Texts and Sequences' course (using NumPy only) by Prof. Yoav Goldberg at Bar-Ilan University
Python implementation of N-gram Models, Log linear and Neural Linear Models, Back-propagation and Self-Attention, HMM, PCFG, CRF, EM, VAE
R package for log-multiplicative models, including association models
Bayesian structure learning and classification in decomposable graphical models.
The source code repository for the FactorBase system
Basic exercises of chinese information processing
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