Home » Data Science » Machine Learning » True or False: the start and end vectors are fixed throughout training Q: Practice More Questions From: Information Extraction with NLP Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 2000+ Qs Machine Learning 1000+ Qs Created with Fabric.js 4.6.0 Similar Questions Given the following word vectors and start and end vectors, determine the start and end of the sequence of interest.Let’s say you have a relatively small training set (~5 thousand images). Which training strategy makes the most sense? You find that your training set has 70% negative examples and 30% positive. Which of the following techniques will NOT help for training this imbalanced dataset?Examples of variable names that can be used in R are autos_5 and utility2. Variable names should start with a letter and can also contain numbers and underscores.Which of the following is not true about BERT’s inner word representations? A data analyst wants to communicate to others about their analysis. They ensure the communication has a beginning, a middle, and an end. Then, they confirm that it clearly explains important insights…A data analyst is inserting a line of code directly into their .rmd file. What will they use to mark the beginning and end of the code?A data analyst creates a bar chart with the diamonds dataset. They begin with the following line of code:ggplot(data = diamonds)What symbol should the analyst put at the end of the line of code to add…Fill in the blank: A delimiter is a character that indicates the beginning or end of _____.In what order should the training, validation, and test sets be sampled?Why is it bad to have the same patients in both training and test sets?You’ve fit a random forest of 10 trees with max depth 20. Your training ROC is 0.99 and test ROC is 0.54. Which of the following is NOT a reasonable thing to try?Now let’s say you have a very large dataset (~1 million images). Which training strategies will make the most sense?Let’s say blood pressure (BP) measurements are more likely to be missing among young people, who generally have lower blood pressure. You use mean imputation to train your model. Which option…Assume you have missing data on one of your features, and are considering two options: True or False: "Both options have the same performance". Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 200+ Qs Machine Learning 100+ Qs
