About the client
Our client is an educational website owner who runs a business named trans neuron. He offers skills development courses to working professionals and students.
Business Requirement
The business needed us to create a course and job recommendation system for the users. It should use natural language processing to understand users' needs and find the most relevant results.
Preferable Outcome
To create an ML model that offers relevant suggestions based on students' and working professionals' requirements for courses and jobs, respectively.
Overview of the Project
Our client is a content management services giant who offers services to companies that provide online courses. In this requirement, they wanted to create complete course content along with the final questionnaire to the help of subject matter experts in data collection and exploration. As the test will primarily focus on applicability skills, only 20 out of the 100 questions test the test taker's memory. The rest will focus on the candidate's ability to apply, analyze, and create using their knowledge.
Tools used in the process
Our Contribution
In this project, we were hired to create the ultimate recommendation system for the clients using machine learning technology coupled with natural language processing.
To achieve the goal, we first worked on determining the various needs of the ideal users. Then we started creating solutions, from accumulating data to making the final system continuously improve as it receives more data.
The challenges faced during the process
Problem 1
Scattered Data
The biggest challenge of this project was the amount of scattered data available. Initially, we had to collect various data from the client's websites and other available resources. The data needed to be extended to yield relevant results. But, at the same time handling such a massive amount of data was a challenge on its own.
Solution
To create the perfect model, which started with accumulating all the relevant data available online and through the client. Afterward, we worked on handling and preprocessing the data appropriately to get the best model.
Problem 2
Creating a Higher Accuracy Model
In the initial stages, the model did not offer higher accuracy in the appropriate course and job recommendations.
Solution
To attain higher recommendation model accuracy, we deployed multiple models and then defined data over time to yield better results.
The Final Result
We created the optimized recommendation engine for the business’s client to help them find the most reliable courses and job opportunities.