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#

linear-classifiers

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Лабораторные работы по предмету "Системы и методы принятия решений"

  • UpdatedOct 30, 2022
  • R

Implementation of Parabel (Partitioned Label Trees for Extreme Classification) in Python

  • UpdatedAug 20, 2024
  • Python

Implemented and compared three types of linear classifiers to use for sentiment analysis of Amazon product reviews.

  • UpdatedMay 15, 2021
  • Jupyter Notebook

Built classifiers using logistic regression and decision trees to classify product reviews and used machine learning techniques such as boosting, precision and recall, and stochastic gradient descent for optimization in Python

  • UpdatedJan 20, 2018
  • Jupyter Notebook

Contains code involving CS 503 - Lab 3 : Implementation of Support vector Machine.

  • UpdatedFeb 26, 2020
  • Python

Perceptron, Pseudo Inverse Linear Classifier, SGD, SVM, Batch Gradient Descent, Minibatch Gradient Descent with tensorflow

  • UpdatedNov 22, 2019
  • Python

Portfolio of Jupyter Notebooks demonstrating various ML models/concepts learned and developed during my graduate machine learning course and independently post-grad. Generally, a bottom-up modeling approach with Numpy is used to showcase grasp of mathematical foundation. Higher-level libraries (scikit-learn) used for optimized algo implementations.

  • UpdatedSep 3, 2025
  • Jupyter Notebook

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