Data Structures and Algorithms

A data structure is the physical embodiment of a data type used to store a set of elements logically represented by abstract data types. Depending on the task required to run on this 8 set of elements, a data structure might be preferred over others. For example, B-trees are the preferred data structure for database indices used to retrieve a subset of records from a population of them. Common operations on data structures are retrieval, insertion, update and deletion of a set of elements.

An algorithm is a finite set of instructions that performs a specific computation. Choosing the correct algorithm and data structure for a specific problem may not be obvious. Though Machine Learning libraries and tools employ the optimal algorithms and data structures for a certain computation scenario, there are cases where practicing Data Scientist might need to choose between alternatives. Therefore a solid grounding in algorithms and data structures is expected of Data Scientists in these situations.