Author Archive: Yugesh Verma

Driver Distraction Prediction Using Deep Learning, Machine Learning

Posted on by

Subscribe YouTube For Latest Update Click Here

Buy Now ₹1501

Buy Now Project Report ₹1001

Driver Distraction Prediction Using Machine Learning”, where given driver images, each taken during a car with a driver doing something within the car (texting, eating, talking on the phone, makeup, reaching behind, etc). The goal was to predict the likelihood of what the driving force is doing in each picture.

Driving a car may be a complex task, and it requires complete attention. Distracted driving is any activity that takes away the driver’s attention from the road. Several studies have identified three main sorts of distraction: visual distractions (driver’s eyes off the road), manual distractions (driver’s hands off the wheel) and cognitive distractions (driver’s mind off the driving task).

Dataset details -

  • Image Size - 480 X 640 pixels
  • Training Images count - 22424 images
  • Test Images count - 79726 images
  • Image type - RGB
  • Image field of view - Dashboard images with view of Driver and passenger
  • The 10 classes to predict are:
    • c0: safe driving
    • c1: texting - right
    • c2: talking on the phone - right
    • c3: texting - left
    • c4: talking on the phone - left
    • c5: operating the radio
    • c6: drinking
    • c7: reaching behind
    • c8: hair and makeup
    • c9: talking to passenger
  • Loss - multi-class logarithmic loss

State-Farm-Distracted-Driver-Detection

Kaggle hosted the challenge few years ago which focused on identifying distracted drivers using Computer Vision
Details of challenge can be found here - https://www.kaggle.com/c/state-farm-distracted-driver-detection

Implementation Details

  • DL Model - CNN's build from scratch ( 6 Conv Layer, 5 Dropout Layer, 3 Dense Layer)
  • Framework - Keras / Pytorch version in the process.
  • CNN Model Visualization/Model Interpretability - GradCAM
  • Final Accuracy -Train acc - 99.06%, Val acc-99 .46%

GRAD-CAM implementation for a test image with label drinking

GRAD-CAM is a technique to highlight how a model classifies new instanes by creating a heat map which highlights only the area which has contributed the most in prediction.
As seen in below image model classifies driver as distracted by drinking by highlighting the hand and glass.

 

Multiple Disease Prediction using Machine Learning

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

Multiple Disease Prediction using Machine Learning . This Web App was developed using Python Flask Web Framework . The models won’t to predict the diseases were trained on large Datasets. All the links for datasets and therefore the python notebooks used for model creation are mentioned below during this readme. The WebApp can predict following Diseases:

  • Diabetes
  • Breast Cancer
  • Heart Disease
  • Kidney Disease
  • Liver Disease
  • Malaria
  • Pneumonia

>Models with their Accuracy of Prediction

DiseaseType of ModelAccuracy
DiabetesMachine Learning Model98.25%
Breast CancerMachine Learning Model98.25%
Heart DiseaseMachine Learning Model85.25%
Kidney DiseaseMachine Learning Model99%
Liver DiseaseMachine Learning Model78%
MalariaDeep Learning Model(CNN)96%
PneumoniaDeep Learning Model(CNN)95%

 

Steps to run the WebApp in local Computer

Step-1: Download the files in the repository.
Step-2: Get into the downloaded folder, open command prompt in that directory and install all the dependencies using following command

pip install -r requirements.txt

Step-3: After successfull installation of all the dependencies, run the following command

python app.py

Dataset Links

All the datasets were used from kaggle.

Crime Data Analysis Project in Machine Learning

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

Crime Data Analysis Project in Machine Learning .Crime analyses is one among the important application of knowledge mining. data processing contains many tasks and techniques including Classification, Association, Clustering, Prediction each of them has its own importance and applications It can help the analysts to spot crimes faster and help to form faster decisions.
The main objective of crime analysis is to seek out the meaningful information from great deal of knowledge and disseminates this information to officers and investigators within the field to help in their efforts to apprehend criminals and suppress criminal activity. In this project, Kmeans Clustering is employed for crime data analysis.

Technologies Used

Web Technologies

Html , Css , JavaScript , Bootstrap , Django

Machine Learning Library In Python

Numpy , Pandas , Scipy
matplotlib
scikit-learn
seaborn

Database

SQLite

Supported Operating System :-

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 3.6.10, PIP, Django.
  4. 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 Step : -

  1. python 3.6.8
  2. command 1 - python -m pip install --user -r requirements.txt
  3. command 2 - python app.py

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.

Movie Recommendation System Project Using Collaborative Filtering, Python Django, Machine Learning

Posted on by

Subscribe YouTube For Latest Update Click Here

Latest Machine Learning Project with Source Code

Buy Now ₹2501

( Note : Project Included with Complete Source code Database Plus Documentation, Synopsis, Report)

Recommender systems are one of the most successful and widespread application of machine learning technologies in business. You can find large scale recommender systems in retail, video on demand, or music streaming.

A Web Base user-item Movie Recommendation Engine using Collaborative Filtering By matrix factorizations algorithm and thus the advice supported the underlying concept is that if two persons both liked certian common movies,then the films that one person has liked that the opposite person has not yet watched are often recommended to him.

A recommender system is a type of information recommend movies to user according to their area of interest. Our recommender system provide personalized information by learning the user‟s interests from previous interactions with that user[2]. In pattern recognition, the knearest neighbours algorithm (k-NN) is a flexible method used for classification. In following cases, the input consists of the k closest examples in given space. If k = 1, then the object is simply assigned to the class of that single nearest neighbour.

Project Features :-

  1. User can register and login.
  2. User can search through various movies and look through its details.
  3. User can give rating to the movies.
  4. User can add movie to their watch list.
  5. User can get movie recommendation (Recommendation algorithm (Collaborative Filtering) which suggests new movies based on the ratings given by user.)

Algorithm :

Collabortive Filtering (Recommender Algorithm)

  1. Collaborative filtering filters information by using the interactions and data collected by the system from other users. It's based on the idea that people who agreed in their evaluation of certain items are likely to agree again in the future.

  2. When we want to find a new movie to watch we'll often ask our friends for recommendations. Naturally, we have greater trust in the recommendations from friends who share tastes similar to our own.

  3. Collaborative-filtering systems focus on the relationship between users and items. The similarity of items is determined by the similarity of the ratings of those items by the users who have rated both items.

  4. There are two types of collaborative filtering

    1. User-based, which measures the similarity between target users and other users.
    2. Item-based, which measures the similarity between the items that target users rate or interact with and other items.

    I have used user based collaborative filtering in this project.

Technologies Used

Web Technologies

Html , Css , JavaScript , Bootstrap , Django

Machine Learning Library In Python3

Numpy , Pandas , Scipy

Database

SQLite

Requirements
python 3.7

pip3

virtualenv

Installation

pip install -r requirements.txt --user

Run server locally

$ python manage.py runserver

Go to localhost:8000

  1. Admin email - admin@admin.com
  2. admin pass - admin

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.

Garage Management System PHP MYSQL

Posted on by

Subscribe YouTube For Latest Update Click Here

100 + PHP Projects with Source Code 

Buy Now ₹501

Buy Now Project Report ₹501

This Garage Management System PHP shall help the user to keep track of all the activities in the garage. It is a web based application which shall have users like Manager, Supervisor, Security, Customer and Mechanic. The admin shall give access for specific modules for the other users. The users shall login and manage with the activities of the system. The supervisor shall be able to check for the inventory of vehicle spares in the garage. He shall be able to check for the vehicles that are serviced currently and the ones which has to be notified for services. The user also shall be able to note the mechanic shop time hours. The system will also allow the payment for the repair or service done. The system also can check for the vehicle spares that are sold from the garage. The interface is developed using html and PHP. It has user friendly web interface.

The Garage Management System PHP till now was not able to record the service details of vehicles. It was done manually. The inventory of spares is done manually. There was no maintenance history of all the vehicles that were serviced in the garage. The service dates had to be tracked manually and that was a difficult task.

Login User Roles :

  1. Manager
  2. Supervisor
  3. Security
  4. Customer
  5. Mechanic

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) : 

  1. WAMP Server
  2. XAMPP Server Download ( php 5.5)
  3. MAMP Server
  4. LAMP Server

Installation Steps

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

Buy Now ₹501

Flutter Medicine Reminder App Project using Android Studio

Posted on by

A Flutter application, which you can save medicines and app will be send remind when you have to take it 🔔

A few resources to get you started if this is your first Flutter project:

For help getting started with Flutter, view our online documentation, which offers tutorials, samples, guidance on mobile development, and a full API reference.

Used Technology:

  • flutter cupertino icons 📱 link
  • flutter intl 📆 link
  • flutter sqflite 📋 link
  • flutter auto size text 📝 link
  • flutter path 🚀 link
  • flutter local notifications 🔔 link
  • flutter timezone 🕧 link
  • flutter animated text kit 📝 link
  • flutter animated widgets 👁️‍🗨️ link

App features :

  •  Save medicines in local database
  •  Show notification in correct time
  •  Delete medicines

Download Link

 

Flutter Quiz App Project with Source Code

Posted on by

This is a quiz app that generates 3 questions per quiz.The result is finally displayed depending upon the number of questions answered correctly by the user. Questions are saved in lib/ques.dart files in json format. Android Studio IDE use for run this project android emulator.

QuizApp is an Flutter ,  android, IOS  based application, and enables the user to undertake a series of questions on Dart language. The app is user friendly, and the user shall find it extremely easy to answer the multiple-choice questions. At the end of the quiz, a result-report is generated which states the score. The app also presents an option to the current user to play the question-round again or quit in between.

 

 

Download Link

Steps To Run App

  1. cd QUIZ-APP-FLUTTER
  2. flutter run

Generate Output Files

  1. For Android - https://flutter.dev/docs/deployment/android
  2. For Ios- https://flutter.dev/docs/deployment/ios

Getting Started With Flutter

For help getting started with Flutter, view our online documentation, which offers tutorials, samples, guidance on mobile development, and a full API reference.

Flutter Scientific Calculator App Project | Android Studio

Posted on by

A flutter Scientific Calculator is useful for situations where we need to calculate some complex things like logs or trigonometry. In such cases, the normal calculator won’t be useful for us. So therefore, we are here to develop a Scientific Calculator.

The scientific calculator is a type of an electronic calculator in which different complex calculating methods are involved. These methods contain mathematical, scientific and some methods related to engineering. Other than that, the scientific calculators have some features similar to ordinary calculator in which many kinds of basic calculations can be performed like addition, subtraction, multiplication, division etc. The functions which are involved in scientific calculator are scientific notations, floating point values, trigonometric functions, logarithmic function, fraction, factorial etc. The scientific calculator is used in various fields for example in astronomy, geology, physics, chemistry, somehow in biology as well. This calculator is mostly used by the students studying in school, college and university and also engineers of different sectors.

Flutter Scientific calculator application is an Android project built in Android Studio and or you can also use vs code. As you know by the name of the project it functions fully as similar to a normal calculator. Here you can perform all of your calculation with ease. This whole project is designed using Android Studio. Dart programming language is used for field validations. This project also can be implemented in different gadgets like the mobile phones and the watch gears also platform independent .

Requirements to develop project

To develop this application there are certain things that you need to know beforehand. So let us see its requirements and the platform that we’ll use for this project. Let us begin with the tool that we’ll use for our Flutter Scientific Calculator. The latest Version of Android Studio Or VS Code and also Dart and Flutter plugins Shoul  be install will be chosen as the Application Development Platform for it. So, you must be fond of Android Studio VS Code and also Dart and Flutter  and have good hands on it.

Download Link

Life Insurance Management System in PHP

Posted on by

Subscribe YouTube For Latest Update Click Here

100 + PHP Projects with Source Code 

A dashboard website for a Life Insurance Company. Built using PHP, MySQL, HTML, CSS

Login, logout, session, multilevel access, image uploads are implemented here.Features

  • Agents can create clients
  • Agents can only edit and delete info of the client they created
  • Master Agent can create, update, delete all clients and agents info
  • Payment records and nominees can be added and managed by agents

Deploy on localhost

Assuming XAMPP is already installed in your local machine

  1. Clone into your xampp/htdocs folder
  2. Edit the lims/connection.php file with your database username and password
  3. Go to http://localhost/phpmyadmin
  4. Create a database named lims
  5. import the lims.sql file provided in database backup folder
  6. Go to http://localhost if you see a login page, it is working

Download Link

 

Online Voting System in django Python | Django Poll

Posted on by

Django poll app is a full featured polling app. You have to register in this app to show the polls and to vote. If you already voted you can not vote again. Only the owner of a poll can add poll , edit poll, update poll, delete poll , add choice, update choice, delete choice and end a poll. If a poll is ended it can not be voted. Ended poll only shows user the final result of the poll. There is a search option for polls. Also user can filter polls by name, publish date, and by number of voted. Pagination will work even after applying filter.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Latest Python Projects with source code

Prerequisites

python== 3.5 or up and django==2.0 or up

Installing

open terminal and type

onal in project directory and type

python manage.py makemigrations
python manage.py migrate

To use admin panel you need to create superuser using this command

python manage.py createsuperuser

To run the program in local server use the following command

python manage.py runserver

Then go to http://127.0.0.1:8000/home in your browser

 

Download Here

Buy Project Report ₹501