This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 3. Artem, Dimi, Laszlo, and Paulo chose to use Yelp Review dataset for training an NLP model for classifying provided texts as positive or negative reviews. The data includes reviews on restaurants, museums, hospitals, etc., and the number of stars associated with this review (0–5). Team 3 modeled this task as a binary classification problem: determining whether the review is positive (has >=3 stars) or negative (otherwise). Check the diagram Link here., This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 3. Artem, Dimi, Laszlo, and Paulo chose to use Yelp Review dataset for training an NLP model for classifying provided texts as positive or negative reviews. The data includes reviews on restaurants, museums, hospitals, etc., and the number of stars associated with this review (0–5). Team 3 modeled this task as a binary classification problem: determining whether the review is positive (has >=3 stars) or negative (otherwise). Check the diagram Link here. , This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 3. Artem, Dimi, Laszlo, and Paulo chose to use Yelp Review dataset for training an NLP model for classifying provided texts as positive or negative reviews. The data includes reviews on restaurants, museums, hospitals, etc., and the number of stars associated with this review (0–5). Team 3 modeled this task as a binary classification problem: determining whether the review is positive (has >=3 stars) or negative (otherwise). Check the diagram Link here., This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 3. Artem, Dimi, Laszlo, and Paulo chose to use Yelp Review dataset for training an NLP model for classifying provided texts as positive or negative reviews. The data includes reviews on restaurants, museums, hospitals, etc., and the number of stars associated with this review (0–5). Team 3 modeled this task as a binary classification problem: determining whether the review is positive (has >=3 stars) or negative (otherwise). Check the diagram Link here.
