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Related lectures (29)
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Scopes and Lambdas: Data Science with Python
Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.
Quick Sort: In-place Subdivision
Explains the in-place subdivision method for quicksort with a unique pivot, covering its temporal complexity.
Algorithms to Live By: Optimal Stopping and Logarithmic Regret
Explores optimal stopping, explore/exploit, Bayes' Rule, and logarithmic regret in bandit solutions.
Sorting Algorithms: Sorting Methods and Comparison
Explores sorting methods, insertion sort, and algorithm comparison for efficient data organization.
Maps: Key-Value Associations
Covers maps as key-value data structures, including querying, updating, and handling missing values, with practical examples like polynomial representation.
Hashing and Quick Sort
Covers the efficient implementation of hash tables and the Quick Sort algorithm.
Pointers: Strings, Functions, Casting
Covers pointers to strings, functions, and casting in C programming.
Derivatives, O-Notation
Explores derivatives, O-Notation, extrema, and algorithm complexity in Analysis 1.
Recursive Sorting: Merge Sort
Explains recursive sorting using Merge Sort and its linearithmic complexity.
