Author Archive: Yugesh Verma

Heart Disease Prediction using Machine Learning Project

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Machine Learning Project with Source Code

Buy Now ₹1501

Buy Now Project Report ₹1001

Introduction

Heart diseases is a term covering any disorder of the heart. Heart diseases have become a major concern to deal with as studies show that the number of deaths due to heart diseases have increased significantly over the past few decades in India, in fact it has become the leading cause of death in India.

A study shows that from 1990 to 2016 the death rate due to heart diseases have increased around 34 per cent from 155.7 to 209.1 deaths per one lakh population in India.

Thus preventing Heart diseases has become more than necessary. Good data-driven systems for predicting heart diseases can improve the entire research and prevention process, making sure that more people can live healthy lives. This is where Machine Learning comes into play. Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate.

Problem Description :

A dataset is formed by taking into consideration some of the information of 920 individuals. The problem is : based on the given information about each individual we have to calculate that whether that individual will suffer from heart disease.

Dataset :

The Heart disease data set consists of patient data from Cleveland, Hungary, Long Beach and Switzerland. The combined dataset consists of 14 features and 916 samples with many missing values. The features used in here are,

  1. Age : displays the age of the individual.
  2. Sex : displays the gender of the individual using the following format : 1 = male 0 = female.
  3. Chest-pain type : displays the type of chest-pain experienced by the individual using the following format : 1 = typical angina 2 = atypical angina 3 = non - anginal pain 4 = asymptotic
  4. Resting Blood Pressure : displays the resting blood pressure value of an individual in mmHg (unit)
  5. Serum Cholestrol : displays the serum cholestrol in mg/dl (unit)
  6. Fasting Blood Sugar : compares the fasting blood sugar value of an individual with 120mg/dl. If fasting blood sugar > 120mg/dl then : 1 (true) else : 0 (false)
  7. Resting ECG : 0 = normal 1 = having ST-T wave abnormality 2 = left ventricular hyperthrophy
  8. Max heart rate achieved : displays the max heart rate achieved by an individual.
  9. Exercise induced angina : 1 = yes 0 = no
  10. ST depression induced by exercise relative to rest : displays the value which is integer or float.
  11. Peak exercise ST segment : 1 = upsloping 2 = flat 3 = downsloping
  12. Number of major vessels (0-3) colored by flourosopy : displays the value as integer or float.
  13. Thal : displays the thalassemia : 3 = normal 6 = fixed defect 7 = reversable defect
  14. Diagnosis of heart disease : Displays whether the individual is suffering from heart disease or not : 0 = absence 1,2,3,4 = present.

Technologies Used : -

  1. Python 3.7
  2. Pandas
  3. Numpy
  4. Flask

Running the web app

Locally

  • Install requirements
    pip install -r requirements.txt
  • Run flask web app
    python main_file.py

Models used and accuracy

A Random forest classifier achieves an average multi-class classification accuracy of 56-60%(183 test samples). It gets 75-80% average binary classification accuracy(heart disease or no heart disease).

Diabetes Prediction using Machine Learning Project Code

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Machine Learning Project with Source Code

Buy Now Source Code ₹1501

Buy Now Project Report ₹1001

In this Diabetes Prediction using Machine Learning Project Code, the objective is to predict whether the person has Diabetes or not based on various features like Number of Pregnancies, Insulin Level, Age, BMI.The data set that has used in this project has taken from the kaggle . "This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage." and used a simple random forest classifier.

Learning Objectives : -

The following points were the objective of the project (The main intention was to create an end-to-end ML project.)

  1. Data gathering
  2. Descriptive Analysis
  3. Data Visualizations
  4. Data Preprocessing
  5. Data Modelling
  6. Model Evaluation
  7. Model Deployment

Technical Aspect : -

  1. Training a machine learning model using scikit-learn.
  2. Building and hosting a Flask web app.
  3. A user has to put details like Number of Pregnancies, Insulin Level, Age, BMI etc .
  4. Once it get all the fields information , the prediction is displyed on a new page .

Technologies Used : -

  1. Python 3.7
  2. Pandas
  3. Numpy
  4. Flask

 

Datasets

https://www.kaggle.com/uciml/pima-indians-diabetes-database

 

Installation

  1. Download  and unzip it.
  2. After downloading, cd into the flask directory.
  3. Begin a new virtual environment with Python 3 and activate it.
  4. Install the required packages using pip install -r requirements.txt

RUN

  1. Execute the command: python app.py

Online Medicine Shop using NodeJS MYSQL

Posted on by

Buy Now Source Code  ₹1001

Buy Now Project Report ₹1001

Online Medicine Shop using NodeJS MYSQL  . The purpose of the system is to ease the process of ordering/purchasing medicines online as well as directly. The system manages the customers and their orders as well as all the details of medicines (Manufacturer info, Expiry Date, etc.). The system is being developed in NodeJs and is based on relational database MySQL. The system will be made available across all the branches of the store along with the users.

Admin Features : 

  1. Add Medicine , Delete Medicine, Edit Medicine.
  2. Add Category , Delete Category ,  Edit Category
  3. Add Brand, Delete Brand, Edit brand.
  4. See All Order.
  5. Update order Status.
  6. Customer Activate , Deactivate.

User Features :

  1. Register.
  2. Login .
  3. Edit Profile.
  4. Add To Cart.
  5. Purchase Medicine.
  6. Check Purchase Status.

Technologies in Used :-

  1. NodeJs.
  2. JavaScript.
  3. CSS.
  4. HTML.
  5. Mysql.
  6. Bootstrap.

Installation Steps :-

  1. create new mysql database import sql file.
  2. run command npm install .
  3. run Command - npm start .

Read Before Purchase  :

  1. One Time Free Installation Support.
  2. Terms and Conditions on this page: https://projectworlds/terms
  3. We offer Paid Customization installation Support
  4.  If you have any questions please contact  Support Section
  5. Please note that any digital products presented on the website do not contain malicious code, viruses or advertising. You buy the original files from the developers. We do not sell any products downloaded from other sites.
  6. You can download the product after the purchase by a direct link on this page.

 

 

Black Friday Sales Prediction project with source code

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Machine Learning Project with Source Code

Buy Source Code ₹1501

Buy Project Report ₹1001

Black Friday Sales Prediction project with source code . In this project, we are getting to predict what proportion the purchasers will spend during Black Friday, using various features like age, gender, legal status . The dataset we are going to use is the Black Friday dataset from Kaggle which contains about 550068 rows and 12 features that can be downloaded here. We will follow all the steps of a Data Science lifecycle from data collection to model deployment.

This Project contains a jupyter notebook file used to train a CatBoostRegressor model for predicting the amount of sales on a black friday based on several feautures.
The model was then integrated into a flask web application

Technologies Used

Web Technologies

Html , Css , JavaScript , Bootstrap , Django

Machine Learning Library In Python

Numpy , Pandas , Scipy
matplotlib
scikit-learn
seaborn

Dataset Link: https://www.kaggle.com/c/black-friday/data

Training Model File 

model.ipynb

model-checkpoint.ipynb

Output Generated File

catBoost.pkl

Read Before Purchase  :

  1. One Time Free Installation Support.
  2. Terms and Conditions on this page: https://projectworlds/terms
  3. We offer Paid Customization installation Support
  4.  If you have any questions please contact  Support Section
  5. Please note that any digital products presented on the website do not contain malicious code, viruses or advertising. You buy the original files from the developers. We do not sell any products downloaded from other sites.
  6. You can download the product after the purchase by a direct link on this page.

 

 

 

Bus Reservation System Project Python Django

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Python Projects with source code

Buy Now Source Code ₹501

Buy Now Project Report ₹501

Bus Reservation System is a preety basic system developed in Django,SQLite,Python, which is designed to automate the online ticket purchasing through an easy online bus booking system.With the bus ticket reservation system you can manage/book reservations, clients data and passengers lists through its Django admin and book tickets effortlessly through the Bus reservation Website.

Features

  1. Built with Python 3.6, Djang0 2.0 Framework
  2. Styled using Bootstrap4
  3. Uses SQLite
  4. Sign in with the application to start using.
  5. Set up a profile about and manage your details
  6. Search for buses based on source and destination
  7. Booking buses
  8. Cancel bus reservations
  9. View buses booked and cancelled
  10. View available buses listing
  11. Login , Registration
  12. Admin Panel

Technology Used 

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. SQLite : SQLite database has been used as database for the project
  7. Django : Project has been developed over the Django Framework

Supported Operating System

  • We can configure this project on following operating system.
  • Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  • Python 2.7, PIP, Django.
  • Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Installation Steps :-

  • Install Python 3.7 Or Higher
  • Install Django version 2.2.0
  • Finally run cmd - python manage.py runserver

 

 

Online Food Ordering Project JAVA JSP MYSQL

Posted on by

Subscribe YouTube For Latest Update Click Here

Buy Now Source Code ₹501

Buy Now Project Report ₹501

An online food ordering system JAVA JSP MYSQL is a web-based application that stimulates the foodies (customers) to put food orders through internet by locating their favorite restaurant or nearest one.  This application is based on the JAVA, JSP (Java Server Page ), MYSQL  platform.

The online food ordering system JAVA JSP MYSQL provides convenience for the customers. It overcomes the disadvantages of the traditional queuing system. This system increases the takeaway of foods than visitors. Therefore, this system enhances the speed and standardization of taking the order from the customer. The online food ordering system JAVA JSP MYSQL set up menu and the customers easily places the order with a simple mouse click. This system allows the user to select the desired food items from the displayed menu. The use r’s details are maintained confidential because it maintains a separate account for each user. An id and password is provided for each user. Therefore it provides a more secured ordering.

Modules and their requirements :-

User Module :

  1. Login
  2. Registration
  3. View Menu
  4. Order
  5. Order History
  6. Feedback

Admin Module :

  1. Login
  2. View Menu
  3. Add Menu Item
  4. Delete Menu
  5. View All User
  6. View All Order
  7. View All Feedbacks
  8. View Specific User all Order

 

Software Requirements

Technology used:

  1. Front end – JSP
  2. Backend – MYSQL

Software:

  1.  IDE - Netbeans 8.2
  2.  Database support - MySQL 5.7
  3.  Operating system – Windows 8 and above
  4.  Server deployment - Glassfish server

Technology:

  • HTML is integrated in JSP. It provides a means to structure text based information in a document. It allows users to produce web pages that include text, graphics and
    hyperlinks.
  •  Javascript is a scripting language which supports the development of both client and server applications. It is preferred at client side to write programs that can be
    executed by a web browser within the context of a web page.
  •  CSS(Cascading Style Sheets) is a style sheet language used for describing the presentation of a document written in a markup language. Although most often used to set the visual style of web pages and user interfaces written in HTML and XHTML, the language can be applied to any XML document,
  •  SQL is the language used to manipulate relational databases. It is tied closely with the relational model. It is issued for the purpose of data definition and data
    manipulation.
  • Java Server pages is a simple yet powerful technology for creating and maintaining dynamic-content web pages. It is based on the Java programming language. It can be thought of as an extension to servlet because it provides more functionality than servlet A JSP page consists of HTML tags and JSP tags. The jsp pages are easier to maintain than servlet because we can separate designing and
    development.

We require a JDBC connection between the front end and back end components to write

to the database and fetch required data.

Buy Now Source Code ₹501

Buy Now Project Report ₹501

 

Android Attendance Management System documentation, report, synopsis

Android Attendance System Project report, documentation, synopsis

Posted on by

Project link - Attendance Management System android projects

 Buy Report ₹301

Student Attendance Management System app deal with the maintenance of the student’s attendance details. It is generates the attendance of the student on basis of presence in class. It is maintaining daily basis of attendance, the staff will be provide with the separate username and password to make student attendance.
The staff handling the particular subject to responsible to make the attendance for all students.
Only if the student presents the particular date, the attendance will be calculated.
The student attendance report based on monthly and consolidate will be generated.

Chapter 1: Introduction
1.1 Definition:-
Attendance Management System app is software developed for daily student attendance in schools, colleges and institutes. It facilitates to access the attendance information of a particular student in a particular class. The information is sorted by the operators, which will be provided by the teacher for a particular class. This system will also help in evaluating attendance eligibility criteria of a student.

1.2 Purpose:-
The purpose of developing Attendance Management System app is to computerized the tradition way of taking attendance. Another purpose for developing this software is to generate the report automatically at the end of the session or in the between of the session.

1.3 Scope:-
The scope of the project is the system on which the software is installed, i.e. the project is developed as a desktop application, and it will work for a particular institute. But later on the project can be modified to operate it online.

1.4 Overview:-
Attendance Management System app basically has two main modules for proper functioning:-
First module is admin which has right for creating space for new batch. Any entry of new faculty, Updating in subject if necessary, and sending notice.
Second module is handled by the user which can be a faulty or an operator. User has a right of making daily attendance, generating report.

1.5 References:-
An Integrated approach to Software Engineering Approach- Dr. Bharat Bhushan Agrawal
And the other contents to different SRS’s report.

 

Chapter 4: Requirement Specifications

4.1 Hardware Requirements:-
RAM: - 8 GB Hard Disk: - 500 GB
Processor: Intel core i3

4.2 Software Requirements:-
Operating System: Windows 10 Front Design: Android Studio
• Front-End Language: java, Latest Version
• Fast Internet connection

Back-End Language: Mysql

4.3 Functional Requirements: -
Attendance Management System app involves the following functions - Easily track attendance information of students.
Quickly produce attendance bulletin.

 

Hostel Management System Project in Python Django

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Python Projects with source code

Buy Now Source Code ₹501

Buy Now Project Report ₹501

This particular project deals with the issues on managing a hostel and avoids the issues which occur when carried manually.Identification of the drawbacks of the prevailing system results in the designing of computerized system which will be compatible to the prevailing system with the system Which is more user friendly and more GUI oriented. We can improve the efficiency of the system, thus overcome the drawbacks of the existing system.

Features :

  1. Login System.
  2. View Room Details
  3. Book Hostel
  4. Student Registration
  5. Manage Students.
  6. Billing.
  7. User Management.
  8. Room Management.
  9. Meal management.
  10. Cost Management.
  11. Student Management.
  12. Visitor Management .

Technology Used in the project 

  • We have developed this project using the below technology
  • HTML : Page layout has been designed in HTML
  • CSS : CSS has been used for all the desigining part
  • JavaScript : All the validation task and animations has been developed by JavaScript
  • Python : All the business logic has been implemented in Python
  • SQLite : SQLite database has been used as database for the project
  • Django : Project has been developed over the Django Framework

Supported Operating System

  • We can configure this project on following operating system.
  • Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  • Python 3.7, PIP, Django 3.1.3 .
  • Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Requirements.txt File

  • asgiref==3.3.0
  • Django==3.1.3
  • gunicorn==20.0.4
  • pytz==2020.4
  • sqlparse==0.4.1\
  • whitenoise==5.2.0

Django Installation Steps :-

  • Install Python 3.7 Or Higher
  • Install Django version 3.1.3
  • Install all dependencies cmd -python -m pip install --user -r requirements.txt
  • Finally run cmd - python manage.py runserver

 

Online Job portal Project in Python Django with source code

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Python Projects with source code

Online Job portal Project in Python Django with source code. This web application is to be conceived in its current form as a dynamic site-requiring constant updates both from the seekers as well as the companies.
The objective of the project is to enable jobseekers to place their resumes and find appropriate jobs while companies to publish their vacancies and find good candidates.
It enables jobseekers to post their resume, look for jobs, view personal job listings. It will provide various companies to put their vacancy profile on the location and even have an choice to search candidate resumes.
Apart from job-seekers and Companies(Job Provider) there'll be an admin module to manage complete Portal also as jobseeker and corporations .

Online Jop Portal Features

  • Administrator
  • Job Seeker
  • Job Provider
  • Job Search

System Users

  • Administrator
  • Job Seeker
  • Job Provider

ADMINISTRATOR FEATURES

Administrator can manage whole website:

  • Manage complete jobseeker section. Like: activate/deactivate/delete/ edit jobseeker’s information.
  • Admin user can view the jobseeker’s applications for each job.
  • Manage complete employer section. Admin user can activate/deactivate/delete/ edit company information.
  • Manage posted jobs. Like: activate/deactivate/delete/edit posted job.
  • Manage whole website content. Dynamic CMS is included to manage the content of the website.
  • Admin user can send message to any jobseeker or job provider.
  • Admin user can send bulk emails as well.
  • Admin user can manage the skills section. Like: Add or remove skills from the website.
  • Manage newsletters section
  • Manage success stories
  • Admin user can manage and handle the prohibited words for whole website.
  • Admin user can add/edit countries, cities, salaries range, qualification, institutes, job industries, website ads.

JOB PROVIDER / COMPANY FEATURES

After registration job provider can perform following action:

  • Add / Edit company’s profile
  • Post new job vacancies
  • Edit / Deactivate posted jobs
  • Job provider can see the list of jobseekers who has applied for the job
  • Job provider can search jobseekers
  • Job provider can see and download the jobseeker’s resume
  • Job provider can send message to any job seeker

JOB SEEKER FEATURES

After registration job seeker can perform following actions:

  • Search for jobs
  • Apply Online for desire job
  • Add/Edit profile information including qualification, experience, and skills.
  • Build his resume by using CV builder functionality of the website.
  • Upload latest resume.

MAIN WEBSITE(WEBSITE FONT END)

From main website, user can perform following actions:

  • Search jobs on the basis of skills, city, country or job title
  • Register as a jobseeker or as a job provider
  • Login to jobseeker or job provider portal
  • About Us
  • Contact us
  • Recent Jobs

Local environment Install

  1. Clone the repository and install the packages in the virtual env:pip install -r requirements.txt
  2. Add .env file.cp .env.dev.sample .env
  3. Add Github client ID and client secret in the .env file

Run

1.With the venv activate it, execute:

python manage.py collectstatic

Note : Collect static is not necessary when debug is True (in dev mode)

  1. Create initial database:python manage.py migrate
  2. Load demo data (optional):python manage.py loaddata fixtures/app_name_initial_data.json --app app.model_name
  3. Run server:python manage.py runserver

Run test:

python manage.py test

To dump data:

python manage.py dumpdata --format=json --indent 4 app_name > app_name/fixtures/app_name_initial_data.json

 

Download Link