insideBIGDATA

JUNE 4, 2024

Modern data pipeline platform provider Matillion today announced at Snowflake Data Cloud Summit 2024 that it is bringing no-code Generative AI (GenAI) to Snowflake users with new GenAI capabilities and integrations with Snowflake Cortex AI, Snowflake ML Functions, and support for Snowpark Container Services.

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Flipboard

APRIL 23, 2025

The following diagram illustrates how RBAC works with metadata filtering in the vector database. Amazon Bedrock Knowledge Bases performs similarity searches on the OpenSearch Service vector database and retrieves relevant chunks (optionally, you can improve the relevance of query responses using a reranker model in the knowledge base).

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Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Is Deep Learning just another name for AI? Is all AI Deep Learning?

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Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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Pickl AI

FEBRUARY 7, 2025

Summary: Machine Learning and Deep Learning are AI subsets with distinct applications. ML works with structured data, while DL processes complex, unstructured data. ML requires less computing power, whereas DL excels with large datasets. DL demands high computational power, whereas ML can run on standard systems.

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Flipboard

JUNE 26, 2023

These techniques utilize various machine learning (ML) based approaches. In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience.

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Dataconomy

MAY 2, 2023

The machine learning systems developed by Machine Learning Engineers are crucial components used across various big data jobs in the data processing pipeline. Additionally, Machine Learning Engineers are proficient in implementing AI or ML algorithms. Is ML engineering a stressful job?

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AWS Machine Learning Blog

DECEMBER 6, 2023

In this blog post, we’ll explore how to deploy LLMs such as Llama-2 using Amazon Sagemaker JumpStart and keep our LLMs up to date with relevant information through Retrieval Augmented Generation (RAG) using the Pinecone vector database in order to prevent AI Hallucination. Sign up for a free-tier Pinecone Vector Database.

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Database AWS ML ML 125

Data Science Dojo

MAY 18, 2023

In this panel, we will discuss how MLOps can help overcome challenges in operationalizing machine learning models, such as version control, deployment, and monitoring. Additionally, how ML Ops is particularly helpful for large-scale systems like ad auctions, where high data volume and velocity can pose unique challenges.

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Dataconomy

MARCH 3, 2025

Thanks to machine learning (ML) and artificial intelligence (AI), it is possible to predict cellular responses and extract meaningful insights without the need for exhaustive laboratory experiments. These models use knowledge graphs databases of known biological interactionsto infer how a new gene disruption might affect a cell.

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Data Science Dojo

JUNE 14, 2023

Learn how the synergy of AI and ML algorithms in paraphrasing tools is redefining communication through intelligent algorithms that enhance language expression. The most revolutionary technology that enables this is called machine learning. Paraphrasing tools in AI and ML algorithms Machine learning is a subset of AI.

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Data Science Dojo

JUNE 14, 2023

Learn how the synergy of AI and ML algorithms in paraphrasing tools is redefining communication through intelligent algorithms that enhance language expression. The most revolutionary technology that enables this is called machine learning. Paraphrasing tools in AI and ML algorithms Machine learning is a subset of AI.

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insideBIGDATA

JUNE 22, 2023

AWS is investing $100 million in the program, which will connect AWS AI and machine learning (ML) experts with customers around the globe to help them envision, design, and launch new generative AI products, services, and processes. (AWS), an Amazon.com, Inc.

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AWS Machine Learning Blog

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The resulting vectors are stored in OpenSearch Service databases for efficient retrieval and querying.

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The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Reusability & reproducibility: Building ML models is time-consuming by nature. Save vs package vs store ML models Although all these terms look similar, they are not the same.

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IBM Data Science in Practice

NOVEMBER 21, 2022

Leverage the Watson NLP library to build the best classification models by combining the power of classic ML, Deep Learning, and Transformed based models. In this blog, you will walk through the steps of building several ML and Deep learning-based models using the Watson NLP library.

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Dataconomy

DECEMBER 18, 2024

Cybersecurity professionals validate database configurations before processing valuable data, scan the codebase of new applications before their release, investigate incidents, and identify root causes, among other tasks. Since DL falls under ML, this discussion will primarily focus on machine learning.

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DagsHub

NOVEMBER 4, 2024

Introduction: The Art of Deploying ML Systems Machine Learning is a complicated domain. There are several moving pieces in a Machine Learning System and each of them has its own peculiarities and challenges. Since ML became popular in business, the methods and approaches for deploying them have varied.

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

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The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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AWS Machine Learning Blog

DECEMBER 24, 2024

Trainium chips are purpose-built for deep learning training of 100 billion and larger parameter models. Model training on Trainium is supported by the AWS Neuron SDK, which provides compiler, runtime, and profiling tools that unlock high-performance and cost-effective deep learning acceleration.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

With a strong background in AI/ML, Ishan specializes in building Generative AI solutions that drive business value. Marks work covers a wide range of use cases, with a primary interest in generative AI, agents, and scaling ML across the enterprise. Mark holds six AWS certifications, including the ML Specialty Certification.

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AWS Machine Learning Blog

JANUARY 9, 2023

Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets. Deploying ML models at scale with optimized cost and compute efficiencies can be a daunting and cumbersome task. Design patterns for building ML applications.

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ODSC - Open Data Science

APRIL 19, 2023

Deep learning continues to be a hot topic as increased demands for AI-driven applications, availability of data, and the need for increased explainability are pushing forward. So let’s take a quick dive and see some big sessions about deep learning coming up at ODSC East May 9th-11th.

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Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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O'Reilly Media

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. What does a modern technology stack for streamlined ML processes look like?

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ODSC - Open Data Science

OCTOBER 17, 2023

But without a strong understanding of deep learning, you’ll have a difficult time getting the most out of the cutting-edge developments in the industry. At ODSC West this October 30th to November 2nd, you’ll build the core knowledge and skills you need with the sessions in the deep learning track , such as the ones listed below.

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Google Research AI blog

FEBRUARY 2, 2023

Great machine learning (ML) research requires great systems. In this post, we provide an overview of the numerous advances made across Google this past year in systems for ML that enable us to support the serving and training of complex models while easing the complexity of implementation for end users.

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Flipboard

FEBRUARY 7, 2023

Amazon SageMaker Studio Lab provides no-cost access to a machine learning (ML) development environment to everyone with an email address. The third notebook shows how pre-trained MONAI deep learning models available on MONAI’s Model Zoo can be downloaded and used to segment TCIA (or your own) DICOM prostate MRI volumes.

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PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

What Zeta has accomplished in AI/ML In the fast-evolving landscape of digital marketing, Zeta Global stands out with its groundbreaking advancements in artificial intelligence. Zeta’s AI innovation is powered by a proprietary machine learning operations (MLOps) system, developed in-house.

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Dataconomy

MARCH 27, 2023

However, while RPA and ML share some similarities, they differ in functionality, purpose, and the level of human intervention required. In this article, we will explore the similarities and differences between RPA and ML and examine their potential use cases in various industries. What is machine learning (ML)?

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AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). These models are based on deep learning architectures such as Transformers, which can capture the contextual information and relationships between words in a sentence more effectively. Why do we need an embeddings model?

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AWS Machine Learning Blog

MAY 25, 2023

The Hugging Face Deep Learning Containers (DLCs), which comes pre-packaged with the necessary libraries, make it easy to deploy the model in SageMaker with just few lines of code. Access permission to the AWS Glue databases and tables are managed by AWS Lake Formation. The following screenshot shows the Data Catalog schema.

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AWS Machine Learning Blog

APRIL 19, 2023

Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products and services. Teams can now deliver robust features once and reuse them many times in a variety of models that may be built by different teams.

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Google Research AI blog

FEBRUARY 21, 2023

With the amazing advances in machine learning (ML) and quantum computing, we now have powerful new tools that enable us to act on our curiosity, collaborate in new ways, and radically accelerate progress toward breakthrough scientific discoveries. You can find other posts in the series here.)

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AWS Machine Learning Blog

JUNE 11, 2024

The diverse and rich database of models brings unique challenges for choosing the most efficient deployment infrastructure that gives the best latency and performance. In these cases, the model sizes are smaller, which means the communication overhead with GPUs or ML accelerator instances outweighs their compute performance benefits.

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