Shakil526563

winning-probability-of-goals-and-corners-in-the-Germany-Bundesliga

Machine learning and ensemble models were used to predict winning probability and high corner kicks in football matches, focusing on data preprocessing, feature selection, and performance evaluation through visualizations.

IPL-Win-Prediction-

The project uses LightGBM and Random Forest models to predict IPL match outcomes, with visualizations like pie charts and bar plots showing toss decision frequencies, top scorers, and seasonal run averages.

Object-Detection-on-My-University-Friends-Using-YOLOv8

In this project, I explored object detection by building a custom Data to detect my three university friends and me.

Image-Preprocessing-Pixel-Comparison-Region-Segmentation-and-Watershed-Morphology

Comprehensive Image Preprocessing: Pixel Intensity Comparison, Region-Based Segmentation, and Watershed Analysis with Morphological Operations

Model-Explainability-with-LIME-and-SHAP-Insights-into-Feature-Importance

"Evaluating Model Performance and Feature Importance: A Comparative Analysis Using LIME and SHAP"

Visual-Explanations-with-Grad-CAM-for-Convolutional-Neural-Networks

"Visual explanations using Grad-CAM are applied to convolutional neural networks (CNNs) to interpret and visualize the model’s decision-making process."

Bangla-News-Categorization-Project-Machine-Learning-Model-

"Bangla News Categorization Project: Leveraging diverse ML models, systematic data processing, and ethical considerations for precise classification. Testing, hyperparameter tuning, and ensemble methods enhance performance, ensuring unbiased categorization in varied contexts."

PlantDoc-Android-app-for-Accurate-plant-disease-diagnosis-using-deep-learning.

Our project aims to design and plan for a user-friendly mobile app using advanced Deep Learning and CNN models. By leveraging a diverse leaf disease dataset, the app enables quick and accurate disease identification from leaf photos.

SDLC-for-Health-Care-Application-Planning-and-Requirements-Analysis

SDLC Planning:Systematically outlines the project's lifecycle stages, ensuring a well-structured development process.The project exhibits a well-rounded approach, encompassing strategic planning, financial analysis, and adaptability, highlighting a commitment to achieving goals and navigating challenges for the success of the startup.

-Visualization-and-Prediction-of-Population-Growth-Rates

The code imports libraries, loads a dataset, and displays basic information. It visualizes data using plots and heatmaps, handles missing values, and scales features. A RandomForestRegressor is trained to make predictions, and its performance is evaluated with metrics like mean squared error and R² score.

Billings-management-system-Java_GUI_Framework

The name of my project is Billing system .Billing system is that project where customers easily paid their bills and show the details his/her product .This project help a both customer and buyer.

library-Management-System-using-Bash-Script-language-

Simple Library management system for my Academic course Project

Machine-Learning-ALgorithms-

To understand machine learning algorithms, I can explore key types and techniques for analyzing and modeling data. This will help me learn how they handle classification, regression, and clustering tasks and apply them to real-world problems

Share_Own_Your-LIfe_Story-Application-using-django-

Anyone can Share his life story and also read other people's life story .

Tuition-wed-Project-by-Django-

Tuition Web is an online platform where teachers can find students and guardians can find teachers based on their preferences. Users log in to view notices and follow instructions to fill out the respective registration forms. Teachers upload their CVs, guardians provide details, and all users can access their personalized list.

Internship-Project-Mentorness_ML_

I have successfully completed two comprehensive projects: one centered on predicting credit card approvals, demonstrating my adeptness in data analysis and predictive modeling, and the other focused on sales forecasting for a furniture store, showcasing my proficiency in forecasting methodologies.

Django-Skin-Cancer-Detection-Project

The project employs deep CNNs for feature extraction from Kaggle skin cancer images, enhancing classification accuracy. Integrated with traditional ML algorithms, the system is deployed in Django, providing a user-friendly web interface for real-time skin cancer predictions and early detection.

Shakil526563

Polycystic-ovary-syndrome-Classification-using-machine-learning-algorithms-

Polycystic-ovary-syndrome-Classification-using-machine-learning-algorithms-Random Forest Classification Test Accuracy: 93% Decision Tree Classification Test Accuracy: 84% KNN Classification Test Accuracy: 71% Naive Bayes Classification Test Accuracy: 84% Logistic Regression Classification Test Accuracy: 84%

Predicted-lung-cancer-disease-with-Decision-Tree-Classifier-

Check the lung cancer level like high, medium and low.

Skin-Cancer-Detection-using-traditional-machines-learning-algorithms-

First Preprocessing image then extracted feature using Deep CNN from skin cancer image in kaggle.Then classifying this using some traditional machine learning algorithms

CRUD-APP-

Creating a CRUD (Create, Read, Update, Delete) app using Flutter involves building a user interface to interact with a database or API.

Simple-Todoapp-design-by-flutter-Android-Studios-

Here's a simple implementation of a to-do list app in Flutter. This app allows users to add tasks, Update task, and delete tasks.

Simple-sumApp-design-by-flutter-Android-Studios-

Simple Calculator, just for summations.

Simple-Counter-App-by-flutter-Android-Studios-

The core idea of a counter app is to have a user interface with a numerical value displayed on the screen, along with buttons to increment and decrement that value. When the user taps the "increment" button,

Practice-Flutter-bootstrap-

Flutter Bootstrap is a package for Flutter that allows you to use the Bootstrap CSS framework in your Flutter projects. This can be useful if you want to create responsive web applications with Flutter that have a similar look and feel to Bootstrap-based web applications.

Practice-with-Responsive-Grid-by-flutter-Android-Studios-

In Flutter, a responsive grid refers to the layout structure used to create a grid of items that adjusts its appearance and arrangement based on the available screen space.

Practice-with-Layout-builder-by-flutter-Android-Studios-

In Flutter, the LayoutBuilder widget is a useful tool for building UI layouts that adapt to the available space dynamically. It's used to create a widget subtree that can respond to the dimensions of its parent widget, allowing you to build responsive and flexible layouts.

Create-design-using-media-query-by-flutter-Android-Studios-

In Flutter, MediaQuery is a utility class that provides access to the current device's screen information and configuration. It allows you to obtain information such as the screen size, orientation, pixel density, and more. With this information,

Create-design-using-flexible_widget-by-java-Android-Studios-

In Flutter, the Flexible widget is used to control how a child widget of a Flex or Row/Column behaves inside the available space. It's typically used in combination with other flex-related widgets like Expanded and Spacer to create flexible and responsive layouts.