Twitter Sentiment Analysis

Last Updated on May 3, 2021

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The main objective of this project to predict the sentiment of tweets like positive or negative. For prediction of this project we use LSTM algorithm.

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Real Time Face Mask Detection In Python

Last Updated on May 3, 2021

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About the Project

This COVID-19 pandemic has raised many concerns regarding health and our environment and to stop them from spreading is wearing mask in public places. Therefore, this issue to be addressed efficiently cannot be possible by humans single handedly.

Here's why:

  • Even if a team of people are gathered it would be difficult to keep a note of all people not wearing masks
  • Manual labor can be reduced and thus reducing the price of expenditure on hiring more people for a job which can be accomplished by machine
  • This can not only be used for mask detection but can be tweaked a bit and then used for attendance manager in workplaces or schools, etc.
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Online Gardening Store

Last Updated on May 3, 2021

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This is a project made in Nodejs, MySQL and some npm packages .The aim of the project is to provide gardening people a easy interface from where they could buy necessities for gardening through online. There are various categories of the products from which the user can buy them.

We have options of adding options into cart, modifying them as well as deleting the required items. We have user authentication also in the application, To make it easier for the customers while making a payment we have an option from where one can directly choose the saved cards for the payment, Taxes are also calculated on the sub total once obtained. As of now no payment integration is done. Once a user submits the order, he/she will also able to see the history of their previous orders.

Once a user registers in the application or even when he/she confirms a order a verification of the order as well as login is sent to the registered email-id and mobile numbers.

For future enhancement we have thought of :-

  • adding a filtering options
  • search feature
  • Take user input through some forms for their requirement and use NLP to retrieve the necessary products
  • A chatbot for the whole application for the customers if they have any queries
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Disease Prediction System

Last Updated on May 3, 2021

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ML-Model-Flask-Deployment

This is a demo project to elaborate how Machine Learn Models are deployed on production using Flask API


Prerequisites

You must have Scikit Learn, Pandas (for Machine Leraning Model) and Flask (for API) installed.


Project Structure

This project has four major parts :

  1. model.py - This contains code fot our Machine Learning model to predict employee salaries absed on trainign data in 'hiring.csv' file.
  2. app.py - This contains Flask APIs that receives employee details through GUI or API calls, computes the precited value based on our model and returns it.
  3. request.py - This uses requests module to call APIs already defined in app.py and dispalys the returned value.
  4. templates - This folder contains the HTML template to allow user to enter employee detail and displays the predicted employee salary.


Running the project

  1. Ensure that you are in the project home directory. Create the machine learning model by running below command -
python model.py

This would create a serialized version of our model into a file model.pkl

  1. Run app.py using below command to start Flask API
python app.py

By default, flask will run on port 5000.

  1. Navigate to URL http://localhost:5000

You should be able to view the homepage as below : 

Enter valid numerical values in all 3 input boxes and hit Predict.

If everything goes well, you should be able to see the predcited salary vaule on the HTML page! 

  1. You can also send direct POST requests to FLask API using Python's inbuilt request module Run the beow command to send the request with some pre-popuated values -
python request.py


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Javascript Form Validation Project

Last Updated on May 3, 2021

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I have made JavaScript Form Validation using HTML/CSS/JavaScript. JavaScript form validation is a technical process where a web-form checks if the information provided by a user is correct. This form can be used for updating your information like name,city,etc. , and then after click on submit button the information which you have updated will be shown.

In the JavaScript Form Validation Project, when the user provides all the data and submits the form, usually by hitting the button, the information is sent to the server and validated. The response of the validator is sent back to the user's computer and it's visualised as either a confirmation message.

JavaScript Form Validation is an important feature of good user experience; by catching invalid data, the user can fix it straight away.


Working of JavaScript Form Validation Project:-

In this Project, when you enter data, the browser and/or the web server will check to see that data is in the correct format and within the constraint set by the application.If the information is correctly formatted, the application allows the data to be submitted and saved in a database.

This project is done by using validation attributes on form elements .These are:-

1 . required :- Specifies whether a form field needs to be filled in before the form can be submitted.

2. type :- Specifies whether the data needs to be a number, an emaill address, or some other specific preset type.

3. pattern :- Specifies a regular expression that defines a pattern the entered data needs to follow.

In this Project, after giving your personal information like your name, your address,etc, and then if you click on submit button , then the information which you have filled will be shown .

If you want to update some information ,then you can also do by clicking on update button.The updated information will be shown.

If you want to delete some record ,then you can also delete it by clicking on delete button.


Duration of Project:- 10 months

My role in this project is of Developer

Skills used :- HTML/CSS/JavaScript


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Hacksat

Last Updated on May 3, 2021

About

Imagine a satellite which enables anyone to avoid thinking in data transfer, energy and all of those nuisances.

What it does

HackSat consists of a prototype for a CubeSat blueprint which will allow anyone who wants to do any experimentation up in outer space to avoid worrying about how to send data or how to provide energy and start thinking about which data will be sent and when they will sent it.

It is also worth noticing that everything will be released under an Open Source License

How we built it

We designed the basic structure, based on the CubeSat specs provided by California Polytechnic State University and used by NASA to send low cost satellites.

We printed the structure by means of a couple 3d printers.

We handcrafted all electronics by using a combination of 3 Arduinos, which required us to search for low consuming components, in order to maximize the battery power, we also work on minimize the energy consumption for the whole satellite.

We opted to use recycled components, like solar panels, cables, battery, converter...

We worked a lot on the data transfer part, so it allows the Sat to be sleeping by the most part, on an effort to increase even more the battery life.

And almost 24hours of nonstop work and a lot of enthusiasm!!

Challenges we ran into

We find mostly challenging the electronics, because our main objective was to get the optimal energy out of our battery and avoid draining it too fast.

Another point worth mentioning was the data transfer between the experiment section and the Sat section, because we wanted to isolate each part as much as possible from the other, so the experiment just need to tell the Sat to send the data and nothing more.

Accomplishments that we are proud of

We are very proud to have accomplished the objective of making a viable prototype, even though we have faced some issues during these days, nonetheless we managed to overcome all of those issues and as a consequence we have grown wiser and our vision has become wider.

What we learned

During the development for HackSat, we have learned a lot about radio transmission, a huge lot about serial port and how to communicate data between 3 different micros, using 2 different protocols.

What's next for HackSat

The first improvement that should be made is fix some issues we encountered with the measures of our designs, which have required some on site profiling.

Another obvious improvement is update the case so it is made of aluminium instead of plastic, which is the first blocking issue at the moment for HackSat to be launched.

Finally, we would change the hardware so it has more dedicated hardware which most likely will allow us to optimise even the battery consumption and global lifespan for the Sat.

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