Predix

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Inspiration

We as students understand the struggle in getting the dream job that we all want. Thus, we wanted to change that by increasing our--or others--chances to get the job.

What it does

Using LinkedIn profiles provided by users, the program uses a machine learning model to calculate the chance of the users getting their dream jobs and what are the things that can be improved for attaining those jobs.

How we built it

We made a LinkedIn profile crawler to get abundant of data sets to train the AI. The AI is trained by finding the pattern in the data sets' education, past work experience, skills, etc. After acquiring a model for the AI, it calculates the user's profile with the model and shows on what the user needs to improve upon.

Challenges we ran into

Building a LinkedIn crawler. LinkedIn pages don't load all the HTML elements automatically, so we didn't know why some elements such as "skills" cannot be retrieved from the profiles. Connecting a python backend to a laravel-react.js frontend

Accomplishments that we're proud of

Building a new LinkedIn crawler (parse it into a JSON file) Using machine learning

What we learned

How to parse different elements from a webpage into a JSON file How to connect python backend to the frontend using laravel framework How to use laravel framework together with React.js

What's next for Predix

Develop the app to be able to predict not only software engineering jobs in the tech companies but also jobs in different fields.

Built With

• ajax
• css3
• html5
• javascript
• laravel
• php
• python
• react