Popular Machine Learning interview questions

Hi, this is list of the most popular machine learning interview questions. You can be asked them while applying for ML Engineer position. For each one I tried to add link with short answer. Hope you will enjoy it.

Describe Binary Classification.
https://www.kdnuggets.com/2017/04/must-know-evaluate-binary-classifier.html

Calculate AUC of an ROC curve.
http://blog.revolutionanalytics.com/2016/11/calculating-auc.html

What does P-Value mean?
https://www.statsdirect.com/help/basics/p_values.htm

Explain Linear Regression, assumptions and math equations.
http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm

Explain Logistic Regression, assumptions and math equations.
https://www.medcalc.org/manual/logistic_regression.php

What is cross validation?
https://www.analyticsvidhya.com/blog/2018/05/improve-model-performance-cross-validation-in-python-r/

What are anomaly detection methods?
https://towardsdatascience.com/a-brief-overview-of-outlier-detection-techniques-1e0b2c19e561

What are time series forecasting techniques?
https://www.analyticsvidhya.com/blog/2018/02/time-series-forecasting-methods/

Explain PCA, assumptions, equations.
https://towardsdatascience.com/a-one-stop-shop-for-principal-component-analysis-5582fb7e0a9c

Explain a probability distribution that is not normal.
http://www.statisticshowto.com/probability-and-statistics/non-normal-distributions/

What is and why use feature selection?
https://machinelearningmastery.com/an-introduction-to-feature-selection/

K-mean and Gaussian mixture model: what is the difference between K-means and EM?
https://www.quora.com/What-is-the-difference-between-K-means-and-the-mixture-model-of-Gaussian

Difference between convex and non-convex cost function, what does it mean when a cost function is non-convex?
https://www.researchgate.net/post/What_is_the_difference_between_convex_and_non-convex_optimization_problems

Is random weight assignment better than assigning same weights to the units in the hidden layer?
https://stackoverflow.com/questions/20027598/why-should-weights-of-neural-networks-be-initialized-to-random-numbers

What is Overfitting?
https://en.wikipedia.org/wiki/Overfitting

Why is gradient checking important?
https://www.coursera.org/learn/machine-learning/lecture/Y3s6r/gradient-checking

Describe Tree, SVM, Random forest and boosting. Talk about their advantage and disadvantages.
https://www.quora.com/What-are-the-advantages-of-different-classification-algorithms

Why is dimension reduction important?
https://www.quora.com/Why-is-dimensionality-reduction-useful

Can you explain the fundamentals of Naive Bayes?
https://www.analyticsvidhya.com/blog/2017/09/naive-bayes-explained/

Define variance
http://www.statisticshowto.com/probability-and-statistics/variance/

Describe the difference between L1 and L2 regularization
http://www.chioka.in/differences-between-l1-and-l2-as-loss-function-and-regularization/

What is random forest? Why is Naive Bayes better?
https://www.quora.com/When-and-why-is-a-naive-Bayes-classifier-a-better-worse-choice-than-a-random-forest-classifier

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