Social Media Tweet Analysis

Last Updated on May 3, 2021

About

An R language project to analyze the tweets of social media using visualization graphs like histogram, bar charts, etc.


Requirement

  • Software : R-Studio, R language


Packages

  • igraph 1.2.6 ---> Network Analysis and Visualization
  • NLP 0.2-1 ---> Natural Languag processing infrastructure
  • tm 0.7-8 ---> text miningoackage
  • base 4.0.5 ---> The R base package
  • dataset 4.0.5 ---> The R dataset
  • graphics 4.0.5 ---> The R graphics
  • grDevices 4.0.5 ---> The R Graphics Devices and Support for Colours and Fonts
  • Methods 4.0.5 --->Formal methods and classes
  • stats 4.0.5 ---> R stats packages
  • utils 4.0.5 ---> The R utils Packages


Output

Output is attached in the video mentioned below

More Details: Social Media Tweet Analysis

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Government Fund Tracking System Using Blockchain

Last Updated on May 3, 2021

About

The main idea behind the project is to track the funds hierarchically i.e from central government to the common man including in this chain. We have considered four hierarchical components which are: Central government, state government, Contractor, resource provider/dealer. In the beginning, the budgets which would get finalized in the house will be uploaded according to their respective category. After funds allocation state government will instigate the required projects by documenting them and will send the document to the central government. Now the Central government will verify the project details and if satisfied, they will grant the project funds to the state government else they can reject the project. After receiving funds from the central government, the state government will open the tenders for the contractor and by proper bidding system the contractor will be chosen for the specific project. As bidding and tender allocation will be carried out by an automation bidding system with no human intervention involved, it would reduce corruption. Government committee will check the amount of work done synchronously and will mark every progress by submitting a brief report to the hierarchical officer, who will add it to the blockchain. In this report the progress can be portrayed in the form of images, videos, written plan of the building or structure, etc. To get the payment the contractor will have to submit a form of his total spendings with proper distribution over the duration. This form details will then be checked by the respective authority of the state government and then will initiate the payment to the contractor. In this way doing work over a period gets paid, this process will repeat until a particular work is being done completely.

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Hotel Management System Using Python

Last Updated on May 3, 2021

About

This Project is done using python 3.x which depicts a front end interface of the hotel management system which is done using GUI interface and has the menu, where the user has a list of choices to select the food he wants and this interface has the food rating section where the user has to give the rating in which the food he took, and this interface is done using basic components of GUI. The GUI I used here is Tkinter, and by using List boxes, buttons, the text box is deployed in this interface, which is user-friendly. This interface is done because the situation of covid is increasing tremendously, to reduce the people frequently going outside for food, this interface has been developed. In this interface, we can also set background color and

font color. Here we can also set the background dimension and in this application, we can also change font sizes and also with rows and columns. This interface asks the user to enter his name, mobile number, email id and also asks whether a user prefers a choice of veg or nonveg and also gives a chance to give the food specification whether he needs the food spicy, salty, and some other and the user can choose whether he needs to pay cash, or online payment either which he can also give food rating and he can also select coupons and apply in this interface.

More Details: HOTEL MANAGEMENT SYSTEM USING PYTHON

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Smart Bag Tracker

Last Updated on May 3, 2021

About

Smart bag is an application-specific design that can be useful for almost everyone in the

society. The loss or mishandling of luggage in airports is increasing nowadays,

tremendously raising its associated costs. It is expected that the constant monitoring

detects possible errors in a timely manner, allowing a proactive attitude when correcting

this kind of situations. There are several devices in the market but all have some

problems such as power consumption, location, portability, etc. The current research

provides a novel idea to track the luggage in real time with the help of a microcontroller

system, which is wearable and handy. Using wireless communication techniques, the

proposed system has been designed.


The system consists of GPS module which will fetch the current latitude and longitude and

using advanced Wi-Fi enabled microcontroller which will connect to the 4G


hotspot internet and transmit the current location of the bag to the central server. Using an

Android App the user can view the current position of the bag in google maps.


There are a lot of applications to the luggage but all of them are not controlled from the luggage, instead the commands are sent from the mobile phone to the luggage via Machine to Machine communication. The mobile phone has a pre-installed application software with a pre-installed set of instructions. They wait for the user to send the commands. This can either be for tracking its location.




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Convolutional Neural Network Application To Classify Identical Twins(December 2019-March 2020) (Python,Ml)

Last Updated on May 3, 2021

About

-Transfer learning is employed to classify the images of identical twins.

-Transfer learning basically means using the knowledge acquired during a previous problem solving for finding a solution to a new problem in hand.

-Weights and biases values are used with some fine tuning.

-Pre-trained Convolutional Neural Network models which are developed for image recognition tasks on ImageNet data set, provided by Keras API is used as feature extractor preprocessor.

-All these models are proven to be very efficient in image recognition task.They have showcased very high accuracy on ImageNet dataset.The labels they have given for images were highly accurate with very less error percentage.

-Only convolutional base layers are used here,that is fully connected layers are not included here.

-Fully connected layer is not included and a new fully connected layer is addee at the end for the required categorisation of the data.

-During dataset building-collected images of the identical twins.Two categoried were defined in this way.

-VGG19 is used as a standalone program to extract features from the dataset.

-Feature vectors for training dataset is obtained and mean feature vector for both categories were calculated.

-Testing is done by comparing the feature vectors of testing data with mean feature vectors of each category using cosine similarity.

-Obtained a fair accuracy while testing. 

More Details: Convolutional Neural Network Application to classify Identical Twins(December 2019-March 2020) (Python,ML)

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Regression Analysis On Wallmart Sales Data

Last Updated on May 3, 2021

About

One of the leading retail stores in the US, Walmart, would like to predict the sales and demand accurately. There are certain events and holidays which impact sales on each day. There are sales data available for 45 stores of Walmart. The business is facing a challenge due to unforeseen demands and runs out of stock some times, due to the inappropriate machine learning algorithm. An 

ideal ML algorithm will predict demand accurately and ingest factors like economic conditions including CPI, Unemployment Index, etc.

 Walmart runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of all, which are the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks. Part of the challenge presented by this competition is modeling the effects of markdowns on these holiday weeks in the absence of complete/ideal historical data. Historical sales data for 45 Walmart stores located in different regions are available.

 Dataset Description

This is the historical data which covers sales from 2010-02-05 to 2012-11-01, in the file Walmart_Store_sales. Within this file you will find the following fields:

·        Store - the store number

·        Date - the week of sales

·        Weekly_Sales - sales for the given store

·        Holiday_Flag - whether the week is a special holiday week 1 – Holiday week 0 – Non-holiday week

·        Temperature - Temperature on the day of sale

·        Fuel_Price - Cost of fuel in the region

·        CPI – Prevailing consumer price index

·        Unemployment - Prevailing unemployment rate

 Holiday Events

Super Bowl: 12-Feb-10, 11-Feb-11, 10-Feb-12, 8-Feb-13

Labour Day: 10-Sep-10, 9-Sep-11, 7-Sep-12, 6-Sep-13

Thanksgiving: 26-Nov-10, 25-Nov-11, 23-Nov-12, 29-Nov-13

Christmas: 31-Dec-10, 30-Dec-11, 28-Dec-12, 27-Dec-13

 Analysis Tasks

Basic Statistics tasks

1.     Which store has maximum sales

2.     Which store has maximum standard deviation i.e., the sales vary a lot. Also, find out the coefficient of mean to standard deviation

3.     Which store/s has good quarterly growth rate in Q3’2012

4.     Some holidays have a negative impact on sales. Find out holidays which have higher sales than the mean sales in non-holiday season for all stores together

5.     Provide a monthly and semester view of sales in units and give insights

 Statistical Model

For Store 1 – Build prediction models to forecast demand

·        Linear Regression – Utilize variables like date and restructure dates as 1 for 5 Feb 2010 (starting from the earliest date in order). Hypothesize if CPI, unemployment, and fuel price have any impact on sales.

·        Change dates into days by creating new variable.

Select the model which gives best accuracy.

More Details: Regression Analysis on Wallmart Sales Data