INTERVIEW QUESTIONS

Kernel Trick is an approach consisting in the use of kernel functions, operating in a high-dimensional, implicit feature space without ever computing the coordinates of the data in that space, but rather by simply computing the inner products between the images of all pairs of data in the feature space. This operation is often computationally cheaper than the explicit computation … Read more

Jackknife Resampling (Jacknifing) in statistics is a resampling technique especially useful for variance and bias estimation. The jackknife predates other common resampling methods such as the bootstrap. The jackknife estimator of a parameter is found by systematically leaving out each observation from a dataset and calculating the estimate and then finding the average of these calculations. Given a sample of … Read more

Interpolation in the mathematical field of numerical analysis, is a method of constructing new data points within the range of a discrete set of known data points. In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent … Read more

Intercept is the expected mean value of Y when all X=0. If we start with a regression equation with one predictor, X. If X sometimes is equal zero, the intercept is simply the expected mean value of Y at that value. If X never equals zero, then the intercept has no intrinsic meaning. If so, and if X never = … Read more

Information Retrieval (IR) is the action/process of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, searching for metadata that describes data and for databases such as text, image … Read more

Hopfield Network is a form of recurrent artificial neural network. Hopfield networks are classical models of memory and collective processing in networks of abstract McCulloch-Pitts neurons, but they have not been widely used in signal processing as they usually have small memory capacity (scaling linearly in the number of neurons) and are challenging to train, especially on noisy data. Hopfield … Read more

Homoscedastic ‘in statistics, is a definition of a sequence or a vector of random variables if all random variables in the sequence or vector have the same finite variance. This is also known as the homogeneity of variance. The complementary notion is called heteroscedasticity’. Was the above useful? Please share with others on social media. If you want to look … Read more

Heteroscedasticity refers to the circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it. In other words, it refers to data with unequal variability (scatter) across a set of second, predictor variables. Was the above useful? Please share with others on social media. If you want to look … Read more

Gaussian Distribution (Normal Distribution) in probability theory is a very common continuous probability distribution. Normal distribution is important in statistics and is often used in the natural and social sciences to represent real-valued random variables whose distributions are not known. The normal distribution is useful because of the central limit theorem. In its most general form, under some conditions (which … Read more