Message Passing Through Application Using Python

Project Code :TCMAPY354

Objective

In this application, we are building an application for sending a messages using mobile, who are in critical or dangerous positions, by using machine learning and python technologies.

Abstract

Now-a-days spam and crime alert messages is very terrible problem in the society, often causing death. We can save a person, if they can inform to someone in an early stage. In this application we are detecting the kind of messages and classifying the messages based on the priority. Based on the desires of the messages we will response the people who need help. The techniques of machine learning held a significant stand. This prediction can be done very efficiently using ML. By utilizing the machine learning techniques like Logistic regression, Naive Bayes, SVM, with Natural Language Processing identifies significant relations and patterns, from which the data can be extracted. Utilizing ML messages can be predicted in real time.

Keywords: SMS, Naïve Bayes, Disaster, Data Mining, Machine Learning, Classification, NLP.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

HARDWARE SPECIFICATIONS:

  • Processor: I3/Intel
  • Processor RAM: 4GB (min)
  • Hard Disk: 128 GB
  • Key Board: Standard Windows Keyboard
  • Mouse: Two or Three Button Mouse
  • Monitor: Any

SOFTWARE SPECIFICATIONS:

  • Operating System: Windows 7+
  • Server-side Script: Python 3.6+
  • IDE: PyCharm
  • Libraries Used: Pandas, Numpy, sklearn, Flask, Matplotlib.

Learning Outcomes

  • Scope of Real Time Application Scenarios.
  • Objective of the project.
  • How Internet Works.
  • What is a search engine and how browser can work.
  • What type of technology versions are used.
  • Use of HTML , and CSS on UI Designs.
  • Data Parsing Front-End to Back-End.
  • Working Procedure.
  • Introduction to basic technologies used for.
  • How project works.
  • Input and Output modules.
  • Frame work use.
  • About python.
  • What is machine learning.
  • Machine learning algorithms.
  • What is electronic technologies.
  • Implementing support vector machine.
  • Working of Naïve Bayes.
  • Project Development Skills:
    • Problem analyzing skills.
    • Problem solving skills.
    • Creativity and imaginary skills.
    • Programming skills.
    • Deployment.
    • Testing skills.
    • Debugging skills.
    • Project presentation skills.
    • Thesis writing skills.

Demo Video

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