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Hi there πŸ‘‹

This is Hosna Habibi

  • πŸ”­ I’m currently working on Deep Learning Projects
  • 🌱 I’m currently doing research in DL
  • πŸ“« How to reach me: [email protected]
  • ⚑ Fact about me: I'm a fan of learning new languages

Hosna Habibi's Projects

connect-4-with-negamax icon connect-4-with-negamax

The game is played on a vertical screen with eight rows, where players take turns dropping their pieces into one of the columns.The objective is to be the first player to connect four pieces in a row horizontally, vertically, or diagonally.

counter-strike-with-java icon counter-strike-with-java

In this game, the objective for each player is to eliminate other players in a rectangular playground of adjustable size (n*m). The playground contains randomly placed obstacles that change with each round of the game. In the offline mode, three computer-controlled players act as enemies, spawning in random locations on the ground.

dblab-fall2022 icon dblab-fall2022

Repository for the materials of the course named "Darabase Lab" at the University of Guilan, Department of Computer Engineering, presented in Fall 2022.

decision-tree-classifier icon decision-tree-classifier

This project focuses on implementing and analyzing the learning process in decision trees using Connect 4.

halma-with-java icon halma-with-java

In this project, we plan to revisit classic board games with a touch of nostalgia 😊 Our focus is on reviving the beloved game of Halma, bringing it to life in a captivating graphic environment.

knn_and_naive_bayes_with_scikit_learn icon knn_and_naive_bayes_with_scikit_learn

The Purpose of this project is to familiarize with the NaΓ―ve Bayes and K Nearest Neighbor classification methods. Algorithms related to these two methods were implemented and then trained and tested on the Abalone dataset.

multi-label-text-classification icon multi-label-text-classification

The purpose of this project was to deal with Data Labeling, Multi-label Recurrent Neural Classification, Text Processing and Classification Networks.

student-academic-performance-from-scratch icon student-academic-performance-from-scratch

The purpose of this project was to use the structure of neural network from scratch (Neural Networks from Scratch) in order to predict the acceptance or rejection of students according to a set of their characteristics during an academic semester, which then was also done using tensorflow.

tensorflow-student-academic-performance icon tensorflow-student-academic-performance

The purpose of this project is to learn how to use libraries such as Tensorflow and Pytorch and similar in order to predict students' grades according to their sets of characteristics during an academic semester.

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