AWS Machine Learning Blog

APRIL 19, 2023

The DJL was created at Amazon and open-sourced in 2019. About the authors Fred Wu is a Senior Data Engineer at Sportradar, where he leads infrastructure, DevOps, and data engineering efforts for various NBA and NFL products. It is also a fully Apache-2 licensed open-source project and can be found on GitHub.

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Ocean Protocol

FEBRUARY 28, 2024

Simultaneously, build a first-class data pipeline and analytics dapp, to better answer the question “how much $ am I making” and drill-down questions. Continually improve data pipeline and analytics dapp. It’s why we built it in the first place, way back in 2019! Make $ trading: external. Left: C2D Conceptual Flow.

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phData

JANUARY 31, 2024

Utilizing Streamlit as a Front-End At this point, we have all of our data processing, model training, inference, and model evaluation steps set up with Snowpark. Streamlit, an open-source Python package for building web-apps, has grown in popularity since its launch in 2019. Let’s continue by creating a front-end to enable analysts.

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phData

MAY 25, 2023

The December 2019 release of Power BI Desktop introduced a native Snowflake connector that supported SSO and did not require driver installation. Use Power BI’S Native Snowflake Connector You can connect Power BI to Snowflake just like you can connect Power BI to any other database using the native connector that was released in 2019.

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ODSC - Open Data Science

SEPTEMBER 29, 2023

Such growth makes it difficult for many enterprises to leverage big data; they end up spending valuable time and resources just trying to manage data and less time analyzing it. It truly is an all-in-one data lake solution. HPCC Systems and Spark also differ in that they work with distinct parts of the big data pipeline.

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Snorkel AI

JUNE 22, 2023

One of a few milestones was setting up our product engineering arm, QB Labs, towards the latter part of 2019. One should really think of us at the level of doing the technical implementation work around designing, developing and operationally deploying data products and services that use ML. We’re talking about running code.

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Snorkel AI

JUNE 22, 2023

One of a few milestones was setting up our product engineering arm, QB Labs, towards the latter part of 2019. One should really think of us at the level of doing the technical implementation work around designing, developing and operationally deploying data products and services that use ML. We’re talking about running code.

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Data Quality ML ML AI 52

Snorkel AI

JUNE 22, 2023

One of a few milestones was setting up our product engineering arm, QB Labs, towards the latter part of 2019. One should really think of us at the level of doing the technical implementation work around designing, developing and operationally deploying data products and services that use ML. We’re talking about running code.

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Data Quality ML ML AI 52

phData

JANUARY 15, 2024

HITRUST: Meeting stringent standards for safeguarding healthcare data. ISO/IEC 27001, ISO 27017:2015, and ISO 27018:2019: Adhering to international standards for information security. CSA STAR Level 1 (Cloud Security Alliance): Following best practices for security assurance in cloud computing.

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The MLOps Blog

MARCH 20, 2023

However, in scenarios where dataset versioning solutions are leveraged, there can still be various challenges experienced by ML/AI/Data teams. Data aggregation: Data sources could increase as more data points are required to train ML models. Existing data pipelines will have to be modified to accommodate new data sources.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

The Inferentia chip became generally available (GA) in December 2019, followed by Trainium GA in October 2022, and Inferentia2 GA in April 2023. An important part of the data pipeline is the production of features, both online and offline. All the way through this pipeline, activities could be accelerated using PBAs.

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The MLOps Blog

FEBRUARY 27, 2025

Understand your data sources An important part of building ethically sound AI models lies in verifying that your data comes from sources with clear usage rights. Your data pipeline should flag or exclude content from sources with uncertain copyright status.

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Machine Learning Machine Learning AI AI 64

Kaggle

JULY 29, 2020

He previously co-founded and built Data Works into a 50+ person well-respected software services company. In August 2019, Data Works was acquired and Dave worked to ensure a successful transition. David: My technical background is in ETL, data extraction, data engineering and data analytics.

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AWS Machine Learning Blog

DECEMBER 18, 2024

Fastweb , one of Italys leading telecommunications operators, recognized the immense potential of AI technologies early on and began investing in this area in 2019. With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties.

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