Iguazio

DECEMBER 18, 2023

For data science practitioners, productization is key, just like any other AI or ML technology. However, it's important to contextualize generative AI within the broader landscape of AI and ML technologies. By doing so, you can ensure quality and production-ready models. Here’s to a successful 2024!

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The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. How do I develop my body of work?

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phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

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Iguazio

FEBRUARY 8, 2024

To read more about LLMOps and MLOps, checkout the O’Reilly book “Implementing MLOps in the Enterprise” , authored by Iguazio ’s CTO and co-founder Yaron Haviv and by Noah Gift. LLMOps (Large Language Model Operations), is a specialized domain within the broader field of machine learning operations (MLOps). What is LLMOps?

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Snorkel AI

OCTOBER 18, 2023

From onboarding new customers to analyzing pictures or videos of damages for evaluation, machine learning (ML) and AI offer exciting possibilities for optimization and cost-saving across the insurance industry. Claims data is often noisy, unstructured, and multi-modal. Book a demo today.

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Snorkel AI

OCTOBER 18, 2023

From onboarding new customers to analyzing pictures or videos of damages for evaluation, machine learning (ML) and AI offer exciting possibilities for optimization and cost-saving across the insurance industry. Claims data is often noisy, unstructured, and multi-modal. Book a demo today.

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Snorkel AI

OCTOBER 18, 2023

From onboarding new customers to analyzing pictures or videos of damages for evaluation, machine learning (ML) and AI offer exciting possibilities for optimization and cost-saving across the insurance industry. Claims data is often noisy, unstructured, and multi-modal. Book a demo today. See what Snorkel option is right for you.

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Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. The emergence of Large Language Models (LLMs) like OpenAI's GPT , Meta's Llama , and Google's BERT has ushered in a new era in this field. Their mission?

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Flipboard

MARCH 23, 2023

It has helped to write a book. The world is full of uncreative boilerplate content that humans have to write: catalog entries, financial reports, back covers for books (I’ve written more than a few), and so on. At this point, it’s not clear how language models and their outputs fit into copyright law. What Is the Future?

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ML Review

FEBRUARY 26, 2018

Since intentions determine the subsequent domain identification flow, the intention stratum is a necessary first step in initiating contextual and domain data model processes. Mining data for creating knowledge graphs b. The technical framework for AliMe’s intention and matching stratification 2. AAAI Press, 2014: 1586–1592.

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Mlearning.ai

FEBRUARY 13, 2023

where each book represents a record, each chapter represents a field, and each shelf represents a table. These databases are the most common type used today and store data in a structured format using tables, rows, and columns. In this guide, we’ll cover the eight most popular types of databases. and let’s dive in!

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O'Reilly Media

JULY 20, 2021

The framework I’ve found most helpful is Contextual Integrity which was introduced by Helen Nissenbaum in the book Privacy in Context. With enough data, models can be created to “read between the lines” in both helpful and dangerous ways. Privacy is hard to understand. Video games already cater to multiple people’s experiences.

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Heartbeat

SEPTEMBER 7, 2023

Think of it as a meticulously organized lab notebook, but one that can handle the complexity of modern ML workflows. It provides interactive charts and visualizations to help you gain insights into your model’s behavior. Visualization Tools : Visualizing your experiments’ progress is a breeze with Comet.

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Explosion

JUNE 18, 2021

How implement models ML fundamentals training and evaluation improve accuracy use library APIs Python and DevOps What when to use ML decide what models and components to train understand what application will use outputs for find best trade-offs select resources and libraries The “how” is everything that helps you execute the plan.

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Mlearning.ai

JUNE 8, 2023

Vector Embeddings for Developers: The Basics | Pinecone Used geometry concept to explain what is vector, and how raw data is transformed to embedding using embedding model. A few embeddings for different data type For text data, models such as Word2Vec , GLoVE , and BERT transform words, sentences, or paragraphs into vector embeddings.

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AWS Machine Learning Blog

APRIL 29, 2024

In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows. Metaflow’s coherent APIs simplify the process of building real-world ML/AI systems in teams.

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Snorkel AI

MARCH 16, 2023

Today, I will be introducing you to LandingLens, our main product, and taking you through the journey we went through in developing that product and the data-centric approaches we’ve incorporated into the platform. The third objective is to help our customers get the most from their existing ML platforms.

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Snorkel AI

MARCH 16, 2023

Today, I will be introducing you to LandingLens, our main product, and taking you through the journey we went through in developing that product and the data-centric approaches we’ve incorporated into the platform. The third objective is to help our customers get the most from their existing ML platforms.

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