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This repository contains my completed homework assignments for the Machine Learning course offered by the Amirkabir University.

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Machine Learning Course Homeworks 🤖

Welcome to the Machine Learning Course Homeworks repository! This repository contains my completed homework assignments for the Machine Learning course offered by the Amirkabir University.

Course Description

The Machine Learning course is designed to provide students with a comprehensive introduction to machine learning techniques and their applications. Throughout the course, we will explore various topics, such as supervised and unsupervised learning, regression and classification, neural networks, and deep learning.

Folder Structure

Each homework assignment has its own folder within the repository. The folder structure is as follows:

  • Beysian: Classify breast cncer images using Beysian algorithm(MultinomialNB, GaussianNB) and plot confusion matrix and calculate accuracy.
  • Decision Tree: Implement decision tree from scratch (with ID3 algorithm and Entropy & Gini functions) to classify schools due to their provided information.
  • Neural Networks: Estimate the cost of staying in a hotel using NN + CIFAR-10 classification using NN. Try different cost functions and activation function.
  • SVM: Classification on Anuran dataset using SVM algorithm, fine tuning hyperparameters, and using k-fold cross validation.
each folder contains .pdf files of instruction and report of each HW.

Libraries used in this repo:

  • sklearn
  • keras
  • tensorflow
  • matplotlib
  • scipy

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This repository contains my completed homework assignments for the Machine Learning course offered by the Amirkabir University.

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