Data Science interview questions covering Machine Learning , Deep Learning, Natural Language Processing and more.
Dev set or development set in machine learning is nothing but the validation set. Read here for more explanation. Dev set has following requirements: Dev set and test set needs to have same distribution. It is okay to have training and dev set slightly different distributions. However, dev set and test set must satisfy the same…
We use test set such that we build a model that generalizes well on unseen dataset. If we use test set in tuning for hyper-parameters to select the model, we’re indirectly using test set in training or rather, our model has seen the test set. Hence, it is no longer an unseen dataset but already…
Before any model is built for the problem in hand, the entire dataset exists as a single entity. One can start learning from this dataset and use the built models to make predictions on unseen data. The later part is called generalisation in Machine Learning terminology. Training on entire dataset leads to an overfitted model…