Toolbox

Inspiration

We decided that we want a Machine Learning that predicts your marks because of the anxiety of wanting to know how you did on an exam but, for the teachers to create custom learning plans for each student. We also want a note taking app that has a lot of organising features that is also easy to use with many other features on the way mainly due to the fact that note taking is a lot of work and It will be easier on students if these features are already built into the app. After all this is an app for the students by the students.

What it does

This project consists of a mark predictor using a Linear Regression algorithm and a note taking app that has features such as speech recognition easy to use and intuitve controls

Our project idea is to make a note-taking app, this app is special because it has many features that a modern note-taking app has along with many more features. This is done by incorporating a variety of APIs which will then increase the functionality of our app.

Our app idea revolutionizes mordern day note-taking given the circumstances of the global pandemic. It includes structure and revision formats which helps the target demographic to revise and connect the dots between their studies. This particular app includes features like actice recall, highlight text, To-do list and much more. Additionally the application is aesthetically pleasing and user friendly.

For our mark predictor we are using an algorithm that is based off of linear graphs and the slope concept or the equation more famously known as y = mx + b. Where m = slope and b = y-intercept.

Let's say we have a linear graph with a slope of 3/2 and a y-intercept of 5 we will get an equation of y = 3x/2 + 5

And if we want a certain y value for a certain x value such as x = 5 y = ? we can input x into the equation and we can write this as an function: f(x) = 3x/2 + 5

f(5) = 3(5) / 2 + 5 f(5) = 7.5 + 2 f(5) = 9.5

Hence, the y = 9.5 when x = 5

How we built it

We built it using Jupyter notebook and using Django libraries as well as the Tkinter in built library to make this app.

Challenges we ran into

We faced numerous issues including but not limited to the logical erros faced. The libraries used and algorithms used. A major problem for our application was that we had to switch libraries for the functionality of the note-taking app from tkinter to the virtual environment framework of Django. The installation process itself took a lot of time let alone learning the cmd syntax. Another issue we faced was with the accuracy of the linear regression module

Accomplishments that we're proud of

We got the dropdown box of the UI of the note taking app to work after a long time. We also got the Linear Regression algorithm to show higher accuracy after doing some pre-processing to our data.

What we learned

Django works on the concepts of servers and that it runs on a multitude of code files that all run simultaneously. We also learnt how to increase the accuracy of linear regression models as well. We also learnt a lot of things about Tkinter that we didn't know about before

What's next for Toolbox

We are thinking of using a decision tree algorithm next as we might use more features to predict a person's marks. We are also thinking about making it more aesthetically pleasing. We are also doing app specific features such as back linking, toggling, mind maps, improving the speech recognition app, side by side text, improving speech recognition etc.

Built With

• javascript
• jupyter
• python
• tkinter