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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AWS Machine Learning Blog

NOVEMBER 18, 2024

Amazon Bedrock is a fully managed service that provides a single API to access and use various high-performing foundation models (FMs) from leading AI companies. Amazon Bedrock also offers a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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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. Amazon SageMaker Studio – It is an integrated development environment (IDE) for machine learning (ML).

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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

SEPTEMBER 8, 2023

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

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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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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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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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Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. ML-based predictive models nowadays may consider time-dependent components — seasonality, trends, cycles, irregular components, etc. — to

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AWS Machine Learning Blog

SEPTEMBER 29, 2023

In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Identifying crop regions is a core step towards gaining agricultural insights, and the combination of rich geospatial data and ML can lead to insights that drive decisions and actions.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The previous post discussed how you can use Amazon machine learning (ML) services to help you find the best images to be placed along an article or TV synopsis without typing in keywords. Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using ML.

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AWS Machine Learning Blog

JUNE 3, 2024

Kinesis Video Streams makes it straightforward to securely stream video from connected devices to AWS for analytics, machine learning (ML), playback, and other processing. 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.

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AWS Machine Learning Blog

JANUARY 6, 2023

In Part 2 , we demonstrated how to use Amazon Neptune ML (in Amazon SageMaker ) to train the KG and create KG embeddings. This mapping can be done by manually mapping frequent OOC queries to catalog content or can be automated using machine learning (ML). Matthew Rhodes is a Data Scientist I working in the Amazon ML Solutions Lab.

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Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. You’ll have different shapes of these pipelines.

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Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. You’ll have different shapes of these pipelines.

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Mlearning.ai

FEBRUARY 17, 2023

ML algorithms can be broadly divided into supervised learning , unsupervised learning , and reinforcement learning. How is it actually looks in a real life process of ML investigation? In this article, I will cover all of them. Reward(1) or punishment(0).

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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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AWS Machine Learning Blog

DECEMBER 6, 2023

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback.

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AWS Machine Learning Blog

APRIL 5, 2023

Amazon SageMaker Serverless Inference is a purpose-built inference service that makes it easy to deploy and scale machine learning (ML) models. PyTorch is an open-source ML framework that accelerates the path from research prototyping to production deployment. You can use CLIP with Amazon SageMaker to perform encoding.

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The MLOps Blog

DECEMBER 19, 2022

As Data Scientists, we all have worked on an ML classification model. In this article, we will talk about feasible techniques to deal with such a large-scale ML Classification model. In this article, you will learn: 1 What are some examples of large-scale ML classification models? Let’s take a look at some of them.

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Pickl AI

AUGUST 22, 2023

This harmonization is particularly critical in algorithms such as k-Nearest Neighbors and Support Vector Machines, where distances dictate decisions. To start your learning journey in Machine Learning, you can opt for a free course in ML.

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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. The following is a transcript of his presentation, edited lightly for readability. AB : Got it. Thank you.

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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. The following is a transcript of his presentation, edited lightly for readability. AB : Got it. Thank you.

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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. The following is a transcript of his presentation, edited lightly for readability. AB : Got it. Thank you.

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AWS Machine Learning Blog

DECEMBER 10, 2024

We performed a k-nearest neighbor (k-NN) search to retrieve the most relevant embedding matching the question. With generative AI rapidly developing, there are several ways to improve the results and approach the problem. Archana is an aspiring member of the AI/ML technical field community at AWS.

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ODSC - Open Data Science

JANUARY 5, 2024

With the explosion of AI across industries TensorFlow has also grown in popularity due to its robust ecosystem of tools, libraries, and community that keeps pushing machine learning advances. As expected with the rise of AI, machine learning libraries and data science-focused libraries will become the most popular ones of 2023.

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Mlearning.ai

JULY 4, 2023

By exploring a range of classification algorithms, we ultimately identified the k-nearest neighbor (KNN) algorithm as remarkably successful in predicting the races of individuals. BECOME a WRITER at MLearning.ai // invisible ML // Detect AI img Mlearning.ai

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Mlearning.ai

APRIL 6, 2023

⚠ You can solve the below-mentioned questions from this blog ⚠ ✔ What if I am building Low code — No code ML automation tool and I do not have any orchestrator or memory management system ? ✔ how to reduce the complexity and computational expensiveness of ML models ? will my data help in this ? Let’s create a community!

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Google Research AI blog

AUGUST 15, 2023

Effective recommendations that present students with relevant reading material helps keep students reading, and this is where machine learning (ML) can help. ML has been widely used in building recommender systems for various types of digital content, ranging from videos to books to e-commerce items.

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AWS Machine Learning Blog

SEPTEMBER 25, 2024

Generative AI offers new possibilities to address this challenge and can be used by content teams and influencers to enhance their creativity and engagement while maintaining brand consistency. find_similar_items performs semantic search using the k-nearest neighbors (kNN) algorithm on the input image prompt.

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Mlearning.ai

JULY 6, 2023

Some common quantitative evaluations are linear probing , K nearest neighbors (KNN), and fine-tuning. D BECOME a WRITER at MLearning.ai // invisible ML // Detect AI img Mlearning.ai Evaluation Matrix In SSL, the performance evaluation is usually conducted while doing transfer learning in the downstream task.

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Snorkel AI

JANUARY 26, 2023

Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning.

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Snorkel AI

JANUARY 26, 2023

Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning.

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