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Online RTO Management System Project IN PHP

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Online RTO Management system is final year college submit project that is developed in PHP and MYSQL,CSS JAVASCRIPT. It Provide service both user and admin of RTO department.it provide online service to user that can save user time travel. User can apply for new RC(Registration Certificate),new DL(Driving License) Register New vehicle number.

Features OF User

  1. Apply for New LL (Learner License)
  2. Apply for new Dl (Driving License)
  3. Apply for New RC (vehicle Registration Certificate)
  4. Apply for new vehicle registration for temporary
  5. Apply for Duplicate RC (vehicle Registration Certificate)
  6. Apply for Duplicate DL (Driving License)

This all features save user time and travel as well as crowd will be decrease.

Features Of Admin

  1. All types of data manage by admin.
  2. Check user data and for-word to the next process.
  3. Check Application of DL and for-word to user.
  4. Check Information and accept and reject the for of user DL. If Accept User receive driving license other wise user resubmit the data for DL
  5. Check Information and accept and reject the for of user LL. If accept user will be receive temporary LL valid for 6 moths other wise user need to resubmit the data for new LL.
  6. Check Duplicate RC details that user apply if match the information admin can re-assign the new duplicate RC otherwise form will be rejected and user need to resubmit the form online.
  7. Admin receive request for temporary number of new vehicle by user check engine chassis number. then assign new temporary number. If not match by owner admin reject the form and user need to resubmit the form online.

This all features save lots of time and paper work of admin and it is online so all data secure and save in databse.

Brief overview of the technology:

Front end: HTML, CSS, JavaScript

  1. HTML: HTML is used to create and save web document. E.g. Notepad/Notepad++
  2. CSS : (Cascading Style Sheets) Create attractive Layout
  3. Bootstrap : responsive design mobile freindly site
  4. JavaScript: it is a programming language, commonly use with web browsers.

Back end: PHP, MySQL

  1. PHP: Hypertext Preprocessor (PHP) is a technology that allows software developers to create dynamically generated web pages, in HTML, XML, or other document types, as per client request. PHP is open source software.
  2. MySQL: MySql is a database, widely used for accessing querying, updating, and managing data in databases.

Software Requirement(any one)

Installation Steps

1. Download zip file and Unzip file on your local server.
2. Put this file inside "c:/wamp/www/" .
3. Database Configuration
Open phpmyadmin
Create Database named db name.
Import database db name.sql from downloaded folder(inside database)
4. Open Your browser put inside "http://localhost/project folder name/"

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IMDB Sentiment Analysis based on comment Machine Learning

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his is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training and 25,000 for testing. So, predict the number of positive and negative reviews using either classification or deep learning algorithms.

Computer Vision is the branch of the science of computers and software systems which can recognize as well as understand images and scenes. Computer Vision is consists of various aspects such as image recognition, object detection, image generation, image super-resolution and many more. Object detection is widely used for face detection, vehicle detection, pedestrian counting, web images, security systems and self-driving cars. In this project, we are using highly accurate object detection-algorithms and methods such as R-CNN, Fast-RCNN, Faster-RCNN, RetinaNet and fast yet highly accurate ones like SSD and YOLO. Using these methods and algorithms, based on deep learning which is also based on machine learning require lots of mathematical and deep learning frameworks understanding by using dependencies such as TensorFlow, OpenCV, imageai etc, we can detect each and every object in image by the area object in an highlighted rectangular boxes and identify each and every object and assign its tag to the object. This also includes the accuracy of each method for identifying objects.

Requirements.txt

  1. flasgger==0.9.4
  2. Flask==1.0.3
  3. gunicorn==19.9.0
  4. itsdangerous==1.1.0
  5. Jinja2==2.10.1
  6. MarkupSafe==1.1.1
  7. Werkzeug==0.15.5
  8. numpy==1.18.1
  9. scipy==1.4.1
  10. scikit-learn==0.22.1
  11. matplotlib==3.2.1
  12. pandas==1.0.3
  13. nltk==3.4.5

Download Link

 

 

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Salary Prediction using Machine Learning Web App

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Salary Prediction Based on work experience ML Web App. The purpose of this project is to use data transformation and machine learning to create a model that will predict a salary when given years of experience, job type. The purpose of this project is to use data transformation and machine learning to create a model that will predict a salary when given years of experience, job type.

Data The data for this model is fairly simplified as it has very few missing pieces. The raw data consists of a training dataset with the features listed above and their corresponding salaries.

Information Used To Predict Salaries Years Experience: How many years of experience .

This model can be used as a guide when determining salaries since it shows reasonable predictions when given information on years of experience.

Methods Used

  1. Data Analysis and Visualization
  2. Linear Regression
  3. Polynomial Transformation
  4. Ridge Regression
  5. Random Forest

Technologies/Libraries Used

  1. Python 3
  2. Pandas
  3. NumPy
  4. Seaborn
  5. Scikit-learn
  6. Matplotlib
  7. SciPy
  8. Jupyter

Data

The data for this model is fairly simplified as it has very few missing pieces. The raw data consists of a training dataset with the features listed above and their corresponding salaries. Twenty percent of this training dataset was split into a test dataset with corresponding salaries.

There is also a testing dataset that does not have any salary information available and was used as a substitute for real-world data.

Information Used To Predict Salaries

  1. Years Experience: How many years of experience

Overview

  1. This is project predicts the salary of the employee based on the experience.

Model Training :-

    model.py trains and saves the model to the disk.
    model.pkb the pickle model

Run App :-
    app.py contains all the requiered for flask and to manage APIs.

Procedure
Open command Prompt and go to given directory and then run python app.py

Download Link

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Pneumonia Prediction Using chest x-ray Image Machine Learning

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Chest x-ray: An x-ray exam will allow your doctor to see your lungs, heart and blood vessels to help determine if you have pneumonia. When interpreting the x-ray, the radiologist will look for white spots in the lungs (called infiltrates) that identify an infection. Build an algorithm to automatically identify whether a patient is suffering from pneumonia or not by looking at chest X-ray images. The algorithm had to be extremely accurate because lives of people is at stake. This is a Flask web app designed to analyze a chest x-ray and predict whether a person has TB/pneumonia or not.

Models : 

The model is based on a  convolutional neural network that has been trained on a dataset of 800 images from two sources

The model has an overall accuracy of 83% and an F1 score of 80%.

A negative prediction means that the chest X-ray is most likely normal while the contrary is implied by a positive prediction

Environment and tools

  1. flask
  2. tensorflow

Runtime Python Version  : python-3.8.2

Datasets Link

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.

 

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Credit Card Fraud Detection Machine Learning Project

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Frauds in mastercard transactions are common today as most folks are using the mastercard payment methods more frequently. this is often thanks to the advancement of Technology and increase in online transaction leading to frauds causing huge loss . Therefore, there's need for effective methods to scale back the loss. additionally , fraudsters find ways to steal the mastercard information of the user by sending fake SMS and calls, also through masquerading attack, phishing attack then on. This paper aims in using the multiple algorithms of Machine learning like support vector machine (SVM), k-nearest neighbor (Knn) and artificial neural network (ANN) in predicting the occurrence of the fraud. Further, we conduct a differentiation of the accomplished supervised machine learning and deep learning techniques to differentiate between fraud and non-fraud transactions.

link of dataset=https://www.kaggle.com/mlg-ulb/creditcardfraud

The datasets contains credit card transactions over a two day collection period in September 2013 by European cardholders. There are a total of 284,807 transactions, of which 492 (0.172%) are fraudulent.

The dataset contains numerical variables that are the result of a principal components analysis (PCA) transformation. This transformation was applied by the original authors to maintain confidentiality of sensitive information. Additionally the dataset contains Time and Amount, which were not transformed by PCA. The Time variable contains the seconds elapsed between each transaction and the first transaction in the dataset. The Amount variable is the transaction amount, this feature can be used for example-dependant cost-senstive learning. The Class variable is the response variable and indicates whether the transaction was fraudulant.

The dataset was collected and analysed during a research collaboration of Worldline and the Machine Learning Group of Université Libre de Bruxelles (ULB) on big data mining and fraud detection.

Models

  • Applied various classification techniques like :-
  • Logistic Regression Light
  • GBM K Nearest Neighbors (KNN ) Classification
  • Trees Random Forest
  • SVM XGBoost Classifier

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.

 

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Hypo Thyroid Disease prediction Machine Learning Project

Hypo Thyroid Disease prediction Machine Learning Project

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Hypothyroid diseases (underactive thyroid) is a condition in which the body doesn't produce enough of important thyroid hormones. The condition may lead to various symptoms at late ages. More information about the disease is available at https://www.mayoclinic.org/diseases-conditions/hypothyroidism/symptoms-causes/syc-20350284 .

The Data

The data was from: http://archive.ics.uci.edu/ml/datasets/thyroid+disease. I used "allhypo.data" for the analysis. "allhypo.names" contains the column names of the data. Include the info about primary data processing in the Jupyter notebook list below.

set of algorithms performed to carry out the analysis of the "thyroid-disease" database published in the UCI page
URL data source
data: https://archive.ics.uci.edu/ml/machine-learning-databases/thyroid-disease/sick-euthyroid.data
names: https://archive.ics.uci.edu/ml/machine-learning-databases/thyroid-disease/sick-euthyroid.names


Algorithms

  • Naıve Bayes
  • KNN
  • ANN
  • Random Forest
  • SVM
  • FSF
  • PCA
  • LCA

Related sources

Ionita, Irina. (2016). Prediction of Thyroid Disease Using Data Mining Techniques. BRAIN. Broad Research in Artificial Intelligence and Neuroscience. Vol.7. pp.115-124.
URL: https://www.researchgate.net/publication/321145710_Prediction_of_Thyroid_Disease_Using_Data_Mining_Techniques


Ammulu K., Venugopal. (2017). Thyroid Data Prediction using Data Classification Algorithm. IJIRST –International Journal for Innovative Research in Science & Technology. Vol.4. Issue 2. July 2017. ISSN (online): 2349-6010
URL: http://www.ijirst.org/articles/IJIRSTV4I2054.pdf


Geetha K., Santosh S. Eficient Thyroid Disease Classification Using Differential Evolution with SVM. Journal of Theoretical and Applied Information Technology. Vol.88. No.3. E-ISSN: 1817-3195
URL: http://www.jatit.org/volumes/Vol88No3/4Vol88No3.pdf


Banu, Gulmohamed. (2016). Predicting Thyroid Disease using Linear Discriminant Analysis (LDA) Data Mining Technique. Communications on Applied Electronics. 4. 4-6. 10.5120/cae2016651990. URL: https://www.caeaccess.org/research/volume4/number1/banu-2016-cae-651990.pdf


Lou H, Wang L, Duan D, Yang C,Mammadov M (2018) RDE: A novel approach to improve the classification performance and expressivity of KDB. PLoS ONE 13(7): e0199822. URL: https://doi.org/10.1371/journal.pone.0199822

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.
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Android Tetris Game Project with Source Code

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This Tetris game was created with the Android Studio environment, written in Java.

Tetris is a puzzle game in which geometric shapes called "tetrominoes" fall down onto a playing field, and the player has to arrange them to form gapless lines. Pajitnov took inspiration from pentomino, a classic puzzle game consisting of all the different shapes that can be made by combining five squares – 12 in total – with the goal of arranging them in a wooden box like a jigsaw puzzle.
To simplify things, he knocked that down to four squares, thus reducing the number of shapes from 12 to seven. He called the game Tetris, combining the Greek numeral "tetra" (meaning four) and tennis, his favorite sport.
Pajitnov himself was immediately hooked. "I couldn't stop myself from playing this prototype version, because it was very addictive to put the shapes together," he said on the phone from Seattle, where he now lives.

Software Requirement

  1. Android Studio
  2. Latest Version
  3. Internet Connection
  4. Java

Download link

 

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Android Ludo game project with Source code

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You can find a simple android ludo game developed in android studio. This is just sample project to illustrate canvas in android with threading for game development.

This is 2D game developed for a simple stat of game development in android studio. Please go through code and you can understand yourself. If you still face any issues then do post issues and I will try to solve it.

Ludo game

Ludo written in java, java is very comfortable language for game development but Unity game is perfect game engine to implement high level supported games like pubg, subway surfers, Free fire and more. Mostly used for develop video games, web plugin.

Android Ludo  Game Source Code

Here codes are not explained because spaces are not enough, and online visitors also don’t like the code explanation. They expect only source code which is original on ludo. The full coding is java and xml. If you have good knowledge java then you able to easily make money online. We post android article, projects, applications and more on company website. Get the android applications codes, ideas for that,  to download source code & working from Android Studio IDE.

 

Source code Download Link

 Apk File Download zip

 

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GST Billing Project in Python Django with Source Code

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GST invoice is a bill or receipt of items sent or services that a seller or service provider offers to a customer. It specifically lists out the services/products, along with the total amount due. One can check a GST invoice to determine said product or service prices before CGST and SGST are levied on them.

What is a GST bill? As a GST registered dealer, you are required to provide GST Invoices, also known as bills to your clients. An invoice or a bill is a list of goods sent or services provided, along with the amount due for payment. You can create GST compliant invoices FREE of cost using ClearTax Billing Software.

Simplest GST Billing Project in Python Django .

Features :

  • Easily create invoices
  • Manage inventory
  • Keep books and track balances
  • Print Bill.
  • Automatic Tax Calculation.
  • Automatic Gst Calculation.

Installation Steps: 

  • cmd -  virtualenv -p python3 venv
  • cmd-  source venv/bin/activate
  • cmd-  pip install -r requirements.txt
  • cmd  - python manage.py migrate
  • cmd  -python manage.py runserver

Download Link

 

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Beauty Parlour Management System using PHP and MySQL

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Beauty Parlour Management System is essentially a web-based application that's inbuilt Php with CSS, Ajax and js (javascript). And for the backend of the system, SQL server has been used (i.e. Database) in order that it'll be easy to retrieve later. Also, the most aim of the system is to assist the user to book the appointment within the salon for online.
The system is essentially for the users where they will book a meeting in salon/ salon with login. The users of the system include the customers where they can register initially with the minimum details and will be allowed to make an appointment. Moreover, the system has two panels i.e. Admin and User. The user can make a meeting within the parlour and therefore the admin of the system approves it. Besides, the user also can modify this scheme consistent with their requirements. The user can extract a zipper file containing the ASCII text file and may import into Sublime Text 3 for application development.
Besides, they will also choose the service which they're trying to urge within their specific date and time within the system. All these activities of creating appointments like choosing service also as date and time are going to be recorded within the database for all the events. This project integrates a login panel for a more secure system. Moreover, the system also provides contact details in order that the user has no difficulty in searching the parlour. Besides, the user can visit parlour at a selected date and time because the system already records the appointment made by them.

Brief overview of the technology:

HTML: HTML is used to create and save web document. E.g. Notepad/Notepad++

  1. CSS : (Cascading Style Sheets) Create attractive Layout
  2. JavaScript: it is a programming language, commonly use with web browsers.
  3. Bootstrap: responsive designing.
  4. jQuery

Back end: PHP, MySQL

  1. PHP: Hypertext Preprocessor (PHP) is a technology that allows software developers to create dynamically generated web pages, in HTML, XML, or other document types, as per client request. PHP is open source software.
  2. MySQL: MySql is a database, widely used for accessing querying, updating, and managing data in databases.

Software Requirement(any one)

  • WAMP Server
  • XAMPP Server
  • MAMP Server
  • LAMP Server

Installation Steps

1. Download zip file and Unzip file on your local server.
2. Put this file inside "c:/wamp/www/" .
3. Database Configuration
Open phpmyadmin
Create Database named salon_management.sql.
Import database matrimony.sql from downloaded folder(inside database)
4. Open Your browser put inside "http://localhost/Folder Name/"

User Login

  1. id-ram@gmail.com
  2. Password-ram12345

Staff Id Password

  1. id-dilu@gmail.com
  2. Password-dilu1234

Admin Id password

  1. id-admin
  2. password-admin