Amazon SageMaker is a cloud machine-learning platform that was launched in November 2017. SageMaker enables developers to create, train, and deploy machine-learning models in the cloud. SageMaker also enables developers to deploy ML models on embedded systems and edge-devices.

Amazon SageMaker is a cloud machine-learning platform that was launched in November 2017. SageMaker enables developers to create, train, and deploy machine-learning models in the cloud. SageMaker also enables developers to deploy ML models on embedded systems and edge-devices.

Gittins indices provide an optimal solution to the classical multi-armed bandit problem.The Gittins index is a measure of the reward that can be achieved through a given stochastic process with certain properties

The Gittins index is a measure of the reward that can be achieved through a given stochastic process with certain properties, namely: the process has an ultimate termination state and evolves with an option, at each intermediate state, of terminating.

Multi-armed bandit (MAB) algorithms can be thought of as alternatives to A/B testing that balance exploitation and exploration

In probability theory, the multi-armed bandit problem (sometimes called the K- or N-armed bandit problem) is a problem in which a fixed limited set of resources must be allocated between competing (alternative) choices in a way that maximizes their expected gain, when each choice's properties are only partially known.

Under what scenarios will you choose a simple model over a complex one?

Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is well-suited to the problem of model selection.

When do you think you should retrain a model? Is it dependent on the data?

RETAIN is an interpretable predictive model for healthcare applications. Given patient records, it can make predictions while explaining how each medical code (diagnosis codes, medication codes, or procedure codes) at each visit contributes to the prediction.

MapReduce provides a programming model that abstracts the problem from disk reads and writes, transforming it into computation over sets of keys and values. So, MapReduce is a programming model designed for processing large volumes of data in parallel by dividing the work into a set of independent tasks

MapReduce is the processing layer of Hadoop. MapReduce is a programming model designed for processing large volumes of data in parallel by dividing the work into a set of independent tasks. ... Here in map reduce we get input as a list and it converts it into output which is again a list.

How do access the element in the 2nd column and 4th row of a matrix named M?

The rbind() function in R conveniently adds the names of the vectors to the rows of the matrix. You name the values in a vector, and you can do something very similar with rows and columns in a matrix. For that, you have the functions rownames() and colnames().

What is the difference between a tuple and a list in Python?

List and Tuple in Python are the class of data structure. The list is dynamic, whereas tuple has static characteristics. List are just like the arrays, declared in other ...

What is selection bias? What are its various types?

Selection bias occurs when the study population is not representative of the target ... One way to avoid this type of bias is to restrict the sample to incident cases only. ... If the site is not properly organized, many eligible patients will be excluded.

Any tips

The active argument is a list of active binding functions. ... across packages will not work well, and self and private are not necessary for accessing fields.