Towards AI

MAY 1, 2024

Last Updated on May 1, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. We shall look at various types of machine learning algorithms such as decision trees, random forest, K nearest neighbor, and naïve Bayes and how you can call their libraries in R studios, including executing the code.

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Towards AI

MAY 10, 2024

Last Updated on May 13, 2024 by Editorial Team Author(s): Cristian Rodríguez Originally published on Towards AI. The three weak learner models used for this implementation were k-nearest neighbors, decision trees, and naive Bayes. For the meta-model, k-nearest neighbors were used again.

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Towards AI

JULY 3, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. For geographical analysis, Random Forest, Support Vector Machines (SVM), and k-nearest Neighbors (k-NN) are three excellent methods. So, Who Do I Have?

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Data Science Dojo

JANUARY 30, 2024

Impqct of AI on healthcare The healthcare landscape is brimming with data such as demographics, medical records, lab results, imaging scans, – the list goes on. Nearest neighbor search algorithms : Efficiently retrieving the closest patient vec t o r s to a given query.

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AWS Machine Learning Blog

MARCH 11, 2025

The growing need for cost-effective AI models The landscape of generative AI is rapidly evolving. Although GPT-4o has gained traction in the AI community, enterprises are showing increased interest in Amazon Nova due to its lower latency and cost-effectiveness. Each provisioned node was r7g.4xlarge, About FloTorch FloTorch.ai

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Towards AI

APRIL 4, 2024

Last Updated on April 4, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme.

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Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst?

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ODSC - Open Data Science

FEBRUARY 10, 2025

A/V editing software could offer AI tools that highlight portions of interest in video or audio files for streamlined workflows. AI audio and video systems can alert businesses and homeowners when they detect a potential break-in or other security issue. Any AI solution that listens to or watches people can introduce privacy concerns.

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Pickl AI

MARCH 26, 2024

The K Nearest Neighbors (KNN) algorithm of machine learning stands out for its simplicity and effectiveness. What are K Nearest Neighbors in Machine Learning? Definition of KNN Algorithm K Nearest Neighbors (KNN) is a simple yet powerful machine learning algorithm for classification and regression tasks.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

In the context of generative AI , significant progress has been made in developing multimodal embedding models that can embed various data modalities—such as text, image, video, and audio data—into a shared vector space. He is particularly passionate about AI/ML and enjoys building proof-of-concept solutions for his customers.

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Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. k-NN works by finding the k most similar vectors to a given vector.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. This is the k-nearest neighbor (k-NN) algorithm.

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Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. With the advent of these LLMs or FMs, customers can simply build Generative AI based applications for advertising, knowledge management, and customer support.

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Towards AI

JULY 15, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. We shall look at various machine learning algorithms such as decision trees, random forest, K nearest neighbor, and naïve Bayes and how you can install and call their libraries in R studios, including executing the code.

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Towards AI

NOVEMBER 6, 2024

Author(s): Nilesh Raghuvanshi Originally published on Towards AI. Improving Retrieval Augmented Generation (RAG) Systematically Evaluating the pipeline — AI generated image Introduction This is the third and final article in a short series on systematically improving retrieval-augmented generation (RAG).

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Pickl AI

JANUARY 21, 2025

k-Nearest Neighbors (k-NN) k-NN is a simple algorithm that classifies new instances based on the majority class among its k nearest neighbours in the training dataset. Example: Recommending movies to users based on ratings given by similar users in a collaborative filtering system.

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AWS Machine Learning Blog

FEBRUARY 5, 2025

OpenSearchs vector capabilities help accelerate AI application development, making it easier for teams to operationalize, manage, and integrate AI-driven assets. OpenSearch Service then uses the vectors to find the k-nearest neighbors (KNN) to the vectorized search term and image to retrieve the relevant listings.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Each category necessitates specialized generative AI-powered tools to generate insights. The following is an example of a prompt that can be used to generate Pandas code for data analysis: prompt_template = """ You are an AI assistant designed to answer questions from oil and gas analysts. Put your the code in tags. -

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AWS Machine Learning Blog

SEPTEMBER 8, 2023

You also generate an embedding of this newly written article, so that you can search OpenSearch Service for the nearest images to the article in this vector space. Using the k-nearest neighbors (k-NN) algorithm, you define how many images to return in your results. For this example, we use cosine similarity.

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AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. Prospecting, opportunity progression, and customer engagement present exciting opportunities to utilize generative AI, using historical data, to drive efficiency and effectiveness.

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AWS Machine Learning Blog

APRIL 3, 2024

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. He specializes in Generative AI, Artificial Intelligence, Machine Learning, and System Design.

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Towards AI

JANUARY 26, 2024

Last Updated on January 29, 2024 by Editorial Team Author(s): Shivamshinde Originally published on Towards AI. C can take any positive float value. kernel: This hyperparameter decides which kernel to be used in the algorithm. It can take the values: [‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’, ‘precomputed’].

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Towards AI

APRIL 14, 2023

Last Updated on April 17, 2023 by Editorial Team Author(s): Kevin Berlemont, PhD Originally published on Towards AI. The prediction is then done using a k-nearest neighbor method within the embedding space. Photo by Artem Maltsev on Unsplash Who hasn’t been on Stack Overflow to find the answer to a question?

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Towards AI

FEBRUARY 19, 2025

Last Updated on February 20, 2025 by Editorial Team Author(s): Afaque Umer Originally published on Towards AI. With AI and Large Language Models (LLMs) taking over the world (hopefully not like Skynet 🤖), we need smarter ways to store and retrieve high-dimensional data. Traditional databases? They tap out.

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ODSC - Open Data Science

FEBRUARY 3, 2023

In Aric LaBarr, PhD’s upcoming Ai+ Training session, Anomaly Detection & Introduction to Fraud Modeling , on February 8th, you’ll learn everything you need to detect anomalies and prevent fraud. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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IBM Journey to AI blog

DECEMBER 20, 2023

That’s why diversifying enterprise AI and ML usage can prove invaluable to maintaining a competitive edge. ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. What is machine learning?

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Pickl AI

JULY 31, 2023

Examples of Lazy Learning Algorithms: K-Nearest Neighbors (k-NN) : k-NN is a classic Lazy Learning algorithm used for both classification and regression tasks. The algorithm identifies the k-nearest neighbors, where k is a user-defined parameter that is most similar to the new instance.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Generative AI models for coding companions are mostly trained on publicly available source code and natural language text. Formally, often k-nearest neighbors (KNN) or approximate nearest neighbor (ANN) search is often used to find other snippets with similar semantics.

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Pickl AI

AUGUST 28, 2024

Instead, they memorise the training data and make predictions by finding the nearest neighbour. Examples include K-Nearest Neighbors (KNN) and Case-based Reasoning. Lazy Learners These algorithms do not build a model immediately from the training data. They can handle non-linear data using kernel tricks.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The function then searches the OpenSearch Service image index for images matching the celebrity name and the k-nearest neighbors for the vector using cosine similarity using Exact k-NN with scoring script. Amazon Titan has recently added a new embedding model to its collection, Titan Multimodal Embeddings.

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AWS Machine Learning Blog

APRIL 19, 2024

We perform a k-nearest neighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. However, it highlights the throughput and latency improvements as the main performance advantages of the Inf2 instances over comparable instances for running generative AI models.

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AWS Machine Learning Blog

JUNE 3, 2024

Amazon Bedrock is a fully managed service that provides access to a range of high-performing foundation models from leading AI companies through a single API. It offers the capabilities needed to build generative AI applications with security, privacy, and responsible AI. Victor Wang is a Sr.

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AWS Machine Learning Blog

JANUARY 30, 2024

With the advent of generative AI, today’s foundation models (FMs), such as the large language models (LLMs) Claude 2 and Llama 2, can perform a range of generative tasks such as question answering, summarization, and content creation on text data. Setting k=1 retrieves the most relevant slide to the user question. get('hits')[0].get('_source').get('image_path')

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Pickl AI

JULY 17, 2023

Machine Learning is a subset of artificial intelligence (AI) that focuses on developing models and algorithms that train the machine to think and work like a human. It aims to partition a given dataset into K clusters, where each data point belongs to the cluster with the nearest mean.

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Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. So have you tried other clustering approaches other than K-means, and how does that impact this entire process?

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