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:

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 ...

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