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Md. Surat-E- Mostafa's Projects

basic-pytorch-neural-network-with-iris-dataset icon basic-pytorch-neural-network-with-iris-dataset

The main goal is to develop a model capable of classifying an iris plant based on four features. This is a multi-class classification where each sample can belong to ONE of 3 classes (Iris setosa, Iris virginica or Iris versicolor). The network will have 4 input neurons (flower dimensions) and 3 output neurons (scores). Our loss function will compare the target label (ground truth) to the corresponding output score

bp_prediction_using_ml icon bp_prediction_using_ml

This repository hosts the code for Prediction of Blood Pressure from ECG and PPG signals using ML methods.

c_based_projects icon c_based_projects

This repository contains different kinds of projects using C language with Matlab with detailed explanations.

employee-database-management-in-c-system icon employee-database-management-in-c-system

This is a simple Employee database management system which developed using C++. It utilizes file handling and shows the class and object of the programming language. This project will teach you how to add, list, modify and delete records in file in C++ language. It is very effective and simple understanding for beginners.

estimating-hrv-features icon estimating-hrv-features

# Thesis work: It presents the effect of missing data on HRV analysis and find the optimal method. Besides, it differentiates the different arrythmias based on the spectral entropy value.

logistic-regression-classifier-to-recognize-cats icon logistic-regression-classifier-to-recognize-cats

#Build the general architecture of a learning algorithm, including: Initializing parameters Calculating the cost function and its gradient Using an optimization algorithm (gradient descent) Gather all three functions above into a main model function, in the right order.

neural-network_pytorch_census_income_dataset icon neural-network_pytorch_census_income_dataset

For these exercises I'll perform a binary classification on the Census Income dataset available from the UC Irvine Machine Learning Repository. The goal is to determine if an individual earns more than $50K based on a set of continuous and categorical variables.

pdf_reader icon pdf_reader

#Simple PDF reader: python can read pdf file line by line.

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