[MINI] k-d trees

Where did recommender systems come from, and how do we know when they're actually working? In part one of Data Skeptic's three-part Recommender Systems finale, Kyle traces the field from collaborative filtering and the Netflix Prize to matrix factorization and modern approaches, ...  Show more

Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems, the limitations of optimizing purely for accuracy, and how ideas from social ch ...  Show more

Today we're going to discuss the binary heap data structure. In this episode, you'll learn where to use heaps in practice, how they can come handy to you during a coding interview, and how to implement them! Along the way, we'll cover heap sort, priority queues, load balancing, a ...  Show more

In this episode, we explore foundational algorithms and data structures that every developer and computer science enthusiast should know. Covering everything from Binary Search Trees (BSTs) to advanced concepts like Dynamic Programming and Greedy Algorithms, this episode is packe ...  Show more

In this episode, we'll discuss two fundamental data structures in computer science - arrays and linked lists. Their understanding is essential not only in your day to day job but also for performing well on your next coding interview. We'll discuss implementation details for both ...  Show more

There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they rel ...  Show more