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AMIR'S PORTFOLIO

Here is my portfolio, showcasing some of my different projects.

 * Continue

Amir
 * Linkedin
 * GitHub
 * 

.


FEELING DETECTION

This is a live felling detection model with fined tune EfficientNetB2 model on
FER-13 dataset - will be show up soon

 * Try out (not working yet smile meanwhile :) )


PARALLEL PROGRAMING

In This project different algorithms (Monte Carlo, QickSort, Floyd Warshall)
were implemented using clusters with C programing and OpenMPI

 * See the Code


DATABASE

Designed a database with necessary queries Using SQL. (Click on the image to see
the design or see the repoer from the button below)

 * See more


COMPUTER GRAPHICS

Demonstrating different aspect of computer graphic Using OpenGL and C++
programing.

 * Demo


COMPUTER NETWORKS

This project is a directory manager that works through TCP also it works through
UDP while maiantain its reliability by Selective-Repeat flow using Python
language.

 * See the project


DETECTING COVID-19 USING CHEST X-RAY IMAGES
SED CONSECTETUR

This is a prediction model trained with an imbalance dataset containining Chest
X-ray images (460 covid cases, 1266 Healty, 3418 Pneumonia cases).
We augmented and tackled the imbalance problem witout leackage to our test
dataset and developed multiple coustumes CNN models and pre trained modeled and
compared them to one another using relavent metrics ( precision, recall,
specificity, and F1-Score, as well as accuracy)
We achieved accuracy and a weighted average of 95% on the test. It is a model
that can detect Covid. We did develooped other models with better precision but
the recall is pretty high in this model which is effective at detecting Covid
cases. .

 * See the project


MACHINE LEARNING

In this project multiple datasets were analysed and explored with many different
graphs (see an example), then trained using multiple traditional ML methods

 * See the full project


LOCATION

Canada


GITHUB

github.com/Amir-h055


LINKEDIN

linkedin.com/in/amir--hossein/


EMAIL

amirwork34@gmail.com


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