Hypothesis Testing P values FP, FN Window Functions ROC Decision Tree/Random Forest Past Project
Associate Data Scientist Interview Questions
502 associate data scientist interview questions shared by candidates
Machhine learning questions , Project realted flow, Materix
1. Basics of python Coding. 2. Basics of all the Machine Learning Models. 2. Basic SQL Queries. 3. Brief discussion on the projects you have worked on.
Data science and machine learning basics.
• Your professional snapshot • Data Science Case study, you worked upon • Various techniques used for handling missing values • Assumptions of Regression • ROC, AUC; precision, recall • High recall, low recall • SVM, kmeans • Order of excecution of SQL query
Explain PCA (Wanted me to explain the co-variance matrix and eigen vectors and values and the mathematical expression and mathematical derivation for co-variance matrix)
How would you manipulate data collected on user processes?
How does multiprocessing in work in python?
1.Assumptions of Linear Regression. 2.Outlier detection Methods 3.Handling Missing values
1 Round : Data Frame, ML algorithms, Discussion on your project 2. Case study to develop a model to predict the diamond price 3. Questions based on your case study.
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