Data science questions that come up in placements and interviews — short answers you can say out loud.
Python & data handling
What's the difference between a Python list and a NumPy array?
What does axis=0 vs axis=1 mean?
Series vs DataFrame?
loc vs iloc?
How do you handle missing values?
Machine learning
Supervised vs unsupervised learning?
Why do we split data into train and test sets?
What are overfitting and underfitting?
Precision vs recall?
Decision tree vs random forest?
How does K-Means work, and how do you choose K?
Why is Naive Bayes “naive”?
Text & scraping
Stemming vs lemmatization?
What are stop words, and when should you keep them?
How do you turn text into numbers for a model?
requests + BeautifulSoup vs Selenium — when do you need Selenium?
Quick-fire checklist
File modes r/w/a · os.walk · ndarray vs list · Broadcasting · axis · loc vs iloc · Missing values · groupby · BeautifulSoup find/find_all · Selenium waits · Train/test split · Overfitting · Precision & recall · Random forest · K-Means & elbow · Naive Bayes · Tokenization · Lemmatization · Stop words · Regex · TF-IDF & embeddings