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Implementing Approximate Nearest Neighbor Search with KD-Trees

PyImageSearch

One of the most effective methods to perform ANN search is to use KD-Trees (K-Dimensional Trees). KD-Trees are a type of binary search tree that partitions data points into k-dimensional space, allowing for efficient querying of nearest neighbors. Traditional exact nearest neighbor search methods (e.g.,

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

In this blog, we will explore the details of both approaches and navigate through their differences. A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. What is Generative AI?

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Classifiers in Machine Learning

Pickl AI

Classification is a subset of supervised learning, where labelled data guides the algorithm to make predictions. This blog explores types of classification tasks, popular algorithms, methods for evaluating performance, real-world applications, and why classifiers are indispensable in Machine Learning.

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Five machine learning types to know

IBM Journey to AI blog

Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others. They’re also part of a family of generative learning algorithms that model the input distribution of a given class or/category. Explore the watsonx.ai

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Classification Algorithm in Machine Learning: A Comprehensive Guide

Pickl AI

One of the most fundamental and widely used techniques in Machine Learning is classification. In this blog, we will delve into the world of classification algorithms, exploring their basics, key algorithms, how they work, advanced topics, practical implementation, and the future of classification in Machine Learning.

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Fundamentals of Recommendation Systems

PyImageSearch

This can be especially useful when recommending blogs, news articles, and other text-based content. K-Nearest Neighbor K-nearest neighbor (KNN) ( Figure 8 ) is an algorithm that can be used to find the closest points for a data point based on a distance measure (e.g., That’s not the case.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Journey to AI blog

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.