Movie Collection Predictor

Last Updated on May 3, 2021

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This project predicts the collection of the movie. I have used decision tree regressor model for this project.

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Atm

Last Updated on May 3, 2021

About

Me and my friends have done this project with the help of mentor assigned to us.The project is about the performance of ATM machine developed by Python.


For this project we imported sqlite3 and tkinter as tk. We used Tkinter for GUI applications.Tkinter provides a powerful object-oriented interface to the Tk GUI toolkit. We have created user defined functions such as creating_db, insert_money, insert_atm, check_100, check_200, check_500, check_2000,wd_money, update_bal and main_page. When we run the code the GUI application is created.In this application we can see a note as 'Welcome to ATM' and in the next lines we can see 100/-,200/-,500/- &2000/- notes. If we want to insert money we can click on the option called insert money, if we want to withdraw money we can click on withdraw at the same time if we want to check the availability of respective notes we can click on Check Availability beside the notes. After checking for the availability of notes the result will be displayed on the Python shell. This Python shell is also known as REPL (Read, Evaluate, Print, Loop), where it reads the command, evaluates the command, prints the result, and loop it back to read the command again.For every insert or withdraw update will be done. By using all this we can perform the operation that is required. All this transaction details will be stored in SQLite.


I hope this would be helpful for the public.

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Logisticregression

Last Updated on May 3, 2021

About

Problem Statement :

  • X Education sells online courses to industry professionals. The company markets its courses on several websites and search engines like Google.
  • Once these people land on the website, they might browse the courses or fill up a form for the course or watch some videos. When these people fill up a form providing their email address or phone number, they are classified to be a lead. Moreover, the company also gets leads through past referrals.
  • Once these leads are acquired, employees from the sales team start making calls, writing emails, etc. Through this process, some of the leads get converted while most do not. The typical lead conversion rate at X education is around 30%.

Business Goal:

  • X Education needs help in selecting the most promising leads, i.e. the leads that are most likely to convert into paying customers.
  • The company needs a model wherein you a lead score is assigned to each of the leads such that the customers with higher lead score have a higher conversion chance and the customers with lower lead score have a lower conversion chance.
  • The CEO, in particular, has given a ballpark of the target lead conversion rate to be around 80%.

Strategy

  • Source the data for analysis
  • Clean and prepare the data
  • Exploratory Data Analysis.
  • Feature Scaling ? Splitting the data into Test and Train dataset.
  • Building a logistic Regression model and calculate Lead Score.
  • Evaluating the model by using different metrics - Specificity and Sensitivity or Precision and Recall.
  • Applying the best model in Test data based on the Sensitivity and Specificity Metrics.
  • Solution: 
  • Designed logistic Regression model and calculate the Lead Score 


Key Achievement: 

  • Predicted the leads with a accuracy of 80% and found Important features responsible for good conversion rate or the ones' which contributes more towards the probability of a lead getting converted.
  • Prepared a power point presentation with great visualization for clients and Managers.
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Vehicle Density Based Traffic Optimization/ Management (Ml And Iot)

Last Updated on May 3, 2021

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PROBLEM STATEMENT:

As the vehicle population is rapidly increasing day by day, the cities are facing a huge traffic issue. We know how a traffic system work in current days. Even though there are no vehicles on the green side at the junction, a vehicle on the red side has to wait till the given time. This system has a drawback of traffic delay. On an average most of the junctions in the cities and towns facing this issue

ABSTRACT:

To overcome this problem of over delaying in the traffic, IoT plays a major role. Our idea is: placing IoT sensors at a distance of 100 meters range from the junction we can calculate an average count of vehicles on all the sides. Using this count as main characteristic the traffic light works dynamically that is the roads having high to low count of vehicles has green signal in decreasing order. To increase efficiency of vehicle count we implemented vehicle count using image processing

Tools:

1. Raspberry Pi

2. Camera (web cam)

3. Spyder.

Languages:

1. Python

  

           Vehicle count using image processing

 

Working:

•       At the junction the vehicles coming from different directions may face traffic issues.

•       By image processing technique we can capture the video of number of vehicles coming in different directions.

•       By connecting raspberry pi we can get the count of vehicles in different directions at the junction.

•       Based on the count obtained from different directions the traffic is cleared as per the maximum count of vehicles.

•       The traffic system is prioritized in decreasing order of the count of vehicles ie, the road with high vehicle count will be given first priority and so on.

•       The input in the form of video is captured by web cam, After the vehicle count is done, the control of traffic lights is done using Raspberry Pi

Advantages in real life:

1.Optimizing traffic inconsistency

2.Reducing air pollution

    3.Reducing noise pollution

    4.Priority traffic control

 

My role in the project:

This is a project for HACKATHON where we team of 8 members worked for 2 days. I worked mostly on the coding part for video processing in the project, I also developed an optimized code for prioritizing the traffic lights, this project contains various code segments one for image processing using cv module in python, one for vehicle count and other for prioritization.

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Hotel Management System Using Python

Last Updated on May 3, 2021

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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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Worklet Allocation System

Last Updated on May 3, 2021

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Innovation and Technology have granted numerous opportunities for people around the world who are in need of employment. It has created new marketplaces that offer stable economic benefits which were never thought of before. However, in this modern society, with a plethora of media & mass communication approaches, people offering domestic services still struggle to find jobs on their own and most of them end up joining agencies which take away a significant portion of their income. Services such as home repairs, beauty, and cleaning can be provided at much cheaper rates if the workers are approached directly without any inefficient middlemen.

A web-based home services marketplace is a more convenient and efficient way for people to locate, hire, and provide feedback about nearby domestic employees who are willing to provide their services as per the customer’s requirement. Our proposed system aims to hire skilled workers and connect them to the right clients based on locational proximity. India has a huge demand for these kinds of services and a platform such as this can be used to cater to them.


The aim of this project: to provide a worklet-servicing application, capable of managing its workers employed in a variety of fields as well as its clientele who enlist the services on a day-to-day basis. Our Algorithm aims to match the client to the best service professionals as per their need that is closest to their location in a shorter time period with the help of effective allocation algorithms such as the Shortest Job First and the Banker’s Algorithm. 


Project is built in NodeJS,MongoDB as well as presently algorithm runs in python which needs to called as an API in future enhancements


In this application there are three interfaces Admin,Customer,Client

Client is one who needs the services on a daily basis, Customer is one who needs the services for some period of time in a day.

Admin has the access to the workers data and live tracking of their location where they are working.

To decide for how many hours the service is required we made a questionaire through which a rough estimation of time can be done to allocate the workers.


Future enhancements of the project are -

  • We intend to add the feature where a worker can give their attendance for the day right from within the mobile application and possibly add a chat feature in order to let them communicate with the consumer. 
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