The best approach
We have already seen the intuitive approach for how we will build the best possible approach. Here, we will use the same techniques as the ones we used in the revised approach. In this approach, we are adding more data attributes to make the recommendation engine more accurate. You can refer to the code by using this GitHub link: https://github.com/jalajthanaki/Job_recommendation_engine/blob/master/Job_recommendation_engine.ipynb.
Implementing the best approach
These are the steps we need to take in order to implement the best possible approach:
Filtering the dataset
Preparing the training dataset
Applying the concatenation operation
Generating the TF-IDF and cosine similarity score
Generating recommendations
Let's start implementing each of these listed steps.
Filtering the dataset
In this step, we need to filter the user's dataframe. We are applying the filter on the country data column. We need to consider the US-based users because there are around 300K users based outside...
