Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

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IBM Journey to AI blog

OCTOBER 4, 2023

Typically, on their own, data warehouses can be restricted by high storage costs that limit AI and ML model collaboration and deployments, while data lakes can result in low-performing data science workloads. New insights and relationships are found in this combination. All of this supports the use of AI.

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Metadata AI Strategy Data Scientist Big Data 238

IBM Journey to AI blog

MAY 9, 2023

It drives an AI governance solution without the excessive costs of switching from your current data science platform. The resulting automation drives scalability and accountability by capturing model development time and metadata, offering post-deployment model monitoring, and allowing for customized workflows.

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Metadata Explainability Automation Responsible AI 227

Flipboard

MARCH 7, 2025

Along with each document slice, we store the metadata associated with it using an internal Metadata API, which provides document characteristics like document type, jurisdiction, version number, and effective dates. This process has been implemented as a periodic job to keep the vector database updated with new documents.

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Generative AI Prompt Engineering Prompt Engineer Software Development 151

ODSC - Open Data Science

APRIL 17, 2023

Data security must begin by understanding whether the collected data is compliant with data protection regulations such as GDPR or HIPAA. In this case, the provenance of the collected data is analyzed and the metadata is logged for future audit purposes.

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AWS Machine Learning Blog

OCTOBER 3, 2024

Users without data science or analytics experience can generate rigorous data-backed predictions to answer big questions like time-to-fill for important positions, or resignation risk for crucial employees. The data science team couldn’t roll out changes independently to production.

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DataRobot Blog

MARCH 16, 2023

Traditionally, developing appropriate data science code and interpreting the results to solve a use-case is manually done by data scientists. The integration allows you to generate intelligent data science code that reflects your use case. Data scientists still need to review and evaluate these results.

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AI News

SEPTEMBER 29, 2024

As AI models grow and data volumes expand, databases must scale horizontally, to allow organisations to add capacity without significant downtime or performance degradation. We unify source data, metadata, operational data, vector data and generated data—all in one platform.

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Flipboard

OCTOBER 25, 2023

But most important of all, the assumed dormant value in the unstructured data is a question mark, which can only be answered after these sophisticated techniques have been applied. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. The solution integrates data in three tiers.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

A/B testing and experimentation Data science teams can systematically evaluate different model-tool combinations, measure performance metrics, and analyze response patterns in controlled environments. The role information is also used to configure metadata filtering in the knowledge bases to generate relevant responses.

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Metadata Generative AI ML AI 91

IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance toolkit lets you direct, manage and monitor AI activities without the expense of switching your data science platform, even for models developed using third-party tools.

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Metadata Explainability Automation Explainable AI 220

IBM Journey to AI blog

MAY 9, 2023

Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1] 1] Users can access data through a single point of entry, with a shared metadata layer across clouds and on-premises environments.

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Data Scientist Machine Learning Automation Metadata 276

ODSC - Open Data Science

MARCH 31, 2025

Each text, including the rotated text on the left of the page, is identified and extracted as a stand-alone text element with coordinates and other metadata that makes it possible to render a document very close to the original PDF but from a structured JSONformat.

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Metadata DevOps NLP Large Language Models 52

IBM Journey to AI blog

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data science and MLOps.

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ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

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Data Science ETL Data Scientist Data Quality 52

IBM Journey to AI blog

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

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AWS Machine Learning Blog

MARCH 18, 2025

SQL is one of the key languages widely used across businesses, and it requires an understanding of databases and table metadata. Streamlit This open source Python library makes it straightforward to create and share beautiful, custom web apps for ML and data science. The following diagram illustrates the RAG framework.

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AWS Machine Learning Blog

OCTOBER 28, 2024

Data Scientist at AWS, bringing a breadth of data science, ML engineering, MLOps, and AI/ML architecting to help businesses create scalable solutions on AWS. Publish the BYOC image to Amazon ECR Create a script named model_quality_monitoring.py amazonaws.com/sm-mm-mqm-byoc:1.0", instance_count=1, instance_type='ml.m5.xlarge',

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ML Metadata Data Scientist Machine Learning 107

AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. The solution in this post aims to bring enterprise analytics operations to the next level by shortening the path to your data using natural language. Today, generative AI can enable people without SQL knowledge.

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Metadata LLM Generative AI NLP 133

The MLOps Blog

JUNE 27, 2023

With built-in components and integration with Google Cloud services, Vertex AI simplifies the end-to-end machine learning process, making it easier for data science teams to build and deploy models at scale. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

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Machine Learning Metadata Data Scientist Data Quality 134

IBM Journey to AI blog

JULY 13, 2023

Data science tasks such as machine learning also greatly benefit from good data integrity. When an underlying machine learning model is being trained on data records that are trustworthy and accurate, the better that model will be at making business predictions or automating tasks.

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AWS Machine Learning Blog

MARCH 5, 2025

It stores models, organizes model versions, captures essential metadata and artifacts such as container images, and governs the approval status of each model. He solves complex organizational and technical challenges using data science and engineering. Nick Biso is a Machine Learning Engineer at AWS Professional Services.

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LLM Machine Learning Natural Language Processing Computer Vision 108

IBM Journey to AI blog

OCTOBER 14, 2024

. “Most data being generated every day is unstructured and presents the biggest new opportunity.” ” We wanted to learn more about what unstructured data has in store for AI. Donahue: We’re beginning to see data science and machine learning engineering teams work more closely with data engineering teams.

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ODSC - Open Data Science

FEBRUARY 17, 2025

Metadata tagging and filtering mechanisms safeguard proprietary data. Key Takeaways Data quality is critical for effective RAG implementation. Vector search alone is insufficient; metadata, filtering, and retrieval agents improve accuracy.

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Metadata Machine Learning Data Scientist Data Quality 52

Flipboard

DECEMBER 13, 2024

We discuss the solution components to build a multimodal knowledge base, drive agentic workflow, use metadata to address hallucinations, and also share the lessons learned through the solution development using multiple large language models (LLMs) and Amazon Bedrock Knowledge Bases. Yunfei Bai is a Principal Solutions Architect at AWS.

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Metadata LLM Software Engineer Chatbots 139

Unite.AI

DECEMBER 5, 2023

ETL ( Extract, Transform, Load ) Pipeline: It is a data integration mechanism responsible for extracting data from data sources, transforming it into a suitable format, and loading it into the data destination like a data warehouse. The pipeline ensures correct, complete, and consistent data.

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Metadata Big Data ETL Data Mining 162

AWS Machine Learning Blog

FEBRUARY 19, 2025

In this post, we provide best practices to maximize the value of SageMaker HyperPod task governance and make the administration and data science experiences seamless. Access control When working with SageMaker HyperPod task governance, data scientists will assume their specific role.

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Data Scientist Data Science ML Engineer Generative AI 74

ODSC - Open Data Science

SEPTEMBER 12, 2023

Most data scientists are familiar with the concept of time series data and work with it often. The time series database (TSDB) , however, is still an underutilized tool in the data science community. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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Data Scientist Data Science Metadata Python 97

NVIDIA

JUNE 7, 2024

Finance Organizations Detect Fraud in a Fraction of a Second Financial organizations face a significant challenge in detecting patterns of fraud due to the vast amount of transactional data that requires rapid analysis. Additionally, the scarcity of labeled data for actual instances of fraud poses a difficulty in training AI models.

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Auto-complete Metadata Data Scientist Data Science 126

AWS Machine Learning Blog

AUGUST 22, 2024

It automatically keeps track of model artifacts, hyperparameters, and metadata, helping you to reproduce and audit model versions. In this post, we show you how to convert Python code that fine-tunes a generative AI model in Amazon Bedrock from local files to a reusable workflow using Amazon SageMaker Pipelines decorators.

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AWS Machine Learning Blog

AUGUST 8, 2024

This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock. Twilio’s use case Twilio wanted to provide an AI assistant to help their data analysts find data in their data lake.

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Metadata LLM Prompt Engineering Prompt Engineer 121

AWS Machine Learning Blog

APRIL 12, 2023

With “Science of Gaming” as their core philosophy, they have enabled a vision of end-to-end informatics around game dynamics, game platforms, and players by consolidating orthogonal research directions of game AI, game data science, and game user research. We provided metadata to uniquely distinguish the model from each other.

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AWS Machine Learning Blog

MAY 30, 2024

Each frame will be analyzed using Amazon Rekognition and Amazon Bedrock for metadata extraction. Policy evaluation – Using the extracted metadata from the video, the system conducts LLM evaluation. An Amazon OpenSearch Service cluster stores the extracted video metadata and facilitates users’ search and discovery needs.

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Generative AI Metadata ML AI 131

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

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Data Quality Metadata Big Data ETL 130

DataRobot Blog

SEPTEMBER 1, 2022

These and many other questions are now on top of the agenda of every data science team. To quantify how well your models are doing, DataRobot provides you with a comprehensive set of data science metrics — from the standards (Log Loss, RMSE) to the more specific (SMAPE, Tweedie Deviance). Learn More About DataRobot MLOps.

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Data Drift Data Science AI AI 145

ODSC - Open Data Science

SEPTEMBER 27, 2023

Here are some essential strategies: Time-Stamped Snapshots: Maintaining time-stamped snapshots of the data allows for a historical view of changes made over time. These snapshots can be used to roll back to a previous state or track data lineage. You can connect with her on Linkedin.

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Big Data Metadata ETL Data Science 98

AWS Machine Learning Blog

FEBRUARY 5, 2025

Amazon Kendra also supports the use of metadata for each source file, which enables both UIs to provide a link to its sources, whether it is the Spack documentation website or a CloudFront link. Furthermore, Amazon Kendra supports relevance tuning , enabling boosting certain data sources.

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