India
Yesterday
371
Shocking 😳 Traitor Congress politicians claiming that 26/11 terrorists didn't kill Indian policeman Hemant Karkare
Tech Industry
4d
43014
What happens when most of your team is Indian?
Tech Industry
Yesterday
1189
Question about women in their 30’s?
Software Engineering Career
Yesterday
2980
L4 Google -> 45 interviews, 5 offers, AMA
Tech Industry
Yesterday
1130
The man I love hates me because I’m Vietnamese
Just posted the same Q. When is your interview?
How was the interview? What did they ask?
They gave me a dataset and asked to build a classification model. Practice on any dataset from kaggle, it's an easy round
How'd you proceed? Sklearn? Did you use pipelines? or just raw dogged it? Did you end up using LR / Tree based? Since LR might require standard scaler etc.. ``` df = ... clean_df = pre_processing(df) train_df, test_df = train_test_split(clean_df, ...) model = LogisticRegression.fit(train_df) preds = model.predict(test_df) print(pr_auc(preds, test_df["y"])) ```
I haven't done anything for MLE, but I did do an assessment for an analyst role there. The data they gave me was a mess, and they offered zero clarification on column definitions for ambiguous column names, (I was told that's just what to expect with some data you will see at Stripe). Be prepared to have to do cleanup and make a lot of your own assumptions.