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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