Blog Archives

01: Q01 – Q07 General Big Data, Data Science & Data Analytics Interview Q&As

Q01. How is Big Data used in industries?
A01. The main goal for most organisations is to enhance customer experience, and consequently increase sales. The other goals include cost reduction, better …



02: Cleansing & pre-processing data in BigData & machine learning with Spark interview Q&As

Q1. Why are data cleansing & pre-processing important in analytics & machine learning? A1. Garbage in gets you garbage out. No matter how good your machine learning algorithm is. Q2. What …



03: Simple Linear Regression interview Q&As

Q01. What is a gradient? A01. In algebra we can represent a straight line with: y = mx + c A parabola is represented as: y = m1x2 + m2x + …



04: Residuals, Cost/Loss functions, R-squared & Gradient Descent interview Q&As

Q01. What do you understand by the terms mean, variance, and standard deviation of the sample Vs. the population? A01. Given that the following are the number of job applications sent …



05: Linear regression outputs, null hypothesis, t-test & p-value interview Q&As

Q1. How do you produce & interpret Linear Regression output? A1. Scatter plots can only detect obvious relationships between variables by looking at the graph, but we can use statistics to …



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