seyedamir shobeiri's Projects
we create a banking system using Object Oriented Programming in python
you will learn how to use OpenCV and Deep Learning to detect cars in video streams, track them.
we will check how to obtain video from a webcam and convert it to gray scale, using OpenCV and Python.
This project use Decision tree algorithm in python for classification Patient
As the name of the program suggests, we will be imitating a rolling dice. This is one of the interesting python projects and will generate a random number each dice the program runs, and the users can use the dice repeatedly for as long as he wants. When the user rolls the dice, the program will generate a random number between 1 and 6 (as on a standard dice).
This database contains information about certain drug types.
With advancements in computer vision and deep learning, it is now possible to detect human emotions from images
We will see the basics of face detection and eye detection using the Haar Feature-based Cascade Classifiers
Face detection using Haar cascades is a machine learning based approach where a cascade function is trained with a set of input data. OpenCV already contains many pre-trained classifiers for face, eyes, smiles, etc.. Today we will be using the face classifier. You can experiment with other classifiers as well.
Fashion-MNIST with 88%accuracy
Wildfires are an important phenomenon on a global scale, as they are responsible for large amounts of economic and environmental damage. These effects are being exacerbated by the influence of climate change.It is important to detect fire and warn the people in charge. So you can create Smoke and Fire Detection Algorithms by using this dataset.
A repository focused on enhancing transparency in healthcare machine learning models using SHAP and DeepLIFT. It aims to improve interpretability in medical diagnostics like melanoma and diabetic retinopathy, bridging the gap between AI outputs and clinical decision-making for ethical and trustworthy healthcare AI.
image recognation with Deep learning and GUI
This classification problem is known as the hello world of supervised machine learning
we use MLPclassifier
we implement a multi-layer perceptron to classify the MNIST data. we use MLPClassifier in sklearn.
This dataset includes descriptions of hypothetical samples corresponding to 23 species of gilled mushrooms in the Agaricus and Lepiota Family Mushroom drawn from The Audubon Society Field Guide to North American Mushrooms (1981). Each species is identified as definitely edible, definitely poisonous, or of unknown edibility and not recommended. This latter class was combined with the poisonous one. The Guide clearly states that there is no simple rule for determining the edibility of a mushroom; no rule like "leaflets three, let it be'' for Poisonous Oak and Ivy.
This is one of the simple python projects yet an exciting one. You can even call it a mini-game. Make a program in which the computer randomly chooses a number between 1 to 10, 1 to 100, or any range
we use Breast Cancer Wisconsin (Diagnostic) Data Set
we classification Mnist data set using random forest algorithm
This project is a restaurant menu for microcontrollers and assembly lessons in the university.8086 CPU
we use MLP for classification
my bio for github
Shap library for explaining a Blackbox
I am pleased to announce that our paper entitled “Shapley value in convolutional neural networks (CNNs): A Comparative Study” has been published in the American Journal of Science & Engineering ( AJSE ) and is now accessible online.
I am pleased to announce our newest paper in the IRAQI JOURNAL FOR ELECTRICAL AND ELECTRONIC ENGINEERING (IJEEE) is now published online. Title: ''Shapley Value is an equitable metric for data valuation ''
According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths. This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relavant information about the patient.
One of the best ideas to start experimenting with you hands-on python projects for students is working on a YouTube video downloader