AWS Machine Learning Blog

MARCH 14, 2024

For our final structured and unstructured data pipeline, we observe Anthropic’s Claude 2 on Amazon Bedrock generated better overall results for our final data pipeline. Did anyone make an ace at the 2022 Shriners Children’s Open? Grace Lang is an Associate Data & ML engineer with AWS Professional Services.

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The MLOps Blog

AUGUST 11, 2023

There comes a time when every ML practitioner realizes that training a model in Jupyter Notebook is just one small part of the entire project. Getting a workflow ready which takes your data from its raw form to predictions while maintaining responsiveness and flexibility is the real deal.

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AWS Machine Learning Blog

DECEMBER 6, 2023

If we were to use RAG to converse with these reports, we could ask questions such as “What are the risks that faced company X in 2022,” or “What is the net revenue of company Y in 2022?” Consider the question: “What are the top 5 companies with the highest revenue in 2022?” Sort the revenues in descending order.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

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The MLOps Blog

DECEMBER 7, 2022

2022 will be remembered as a defining year for the crypto ecosystem. And we at deployr , worked alongside them to find the best possible answers for everyone involved and build their Data and ML Pipelines. There’s an old saying in Argentina that goes: “A río revuelto, ganancia de pescadores”.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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IBM Journey to AI blog

AUGUST 11, 2023

Both computer scientists and business leaders have taken note of the potential of the data. Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. MLOps is the next evolution of data analysis and deep learning. What is MLOps?

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AWS Machine Learning Blog

APRIL 12, 2023

The PdMS includes AWS services to securely manage the lifecycle of edge compute devices and BHS assets, cloud data ingestion, storage, machine learning (ML) inference models, and business logic to power proactive equipment maintenance in the cloud. It’s an easy way to run analytics on IoT data to gain accurate insights.

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Pickl AI

NOVEMBER 29, 2024

It enhances scalability, experimentation, and reproducibility, allowing ML teams to focus on innovation. billion in 2022, is expected to soar to USD 505.42 This blog highlights the importance of organised, flexible configurations in ML workflows and introduces Hydra. As the global Machine Learning market, valued at USD 35.80

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phData

JANUARY 31, 2024

In this blog, we’ll show you how to build a robust energy price forecasting solution within the Snowflake Data Cloud ecosystem. We’ll cover how to get the data via the Snowflake Marketplace, how to apply machine learning with Snowpark , and then bring it all together to create an automated ML model to forecast energy prices.

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Iguazio

OCTOBER 20, 2024

The webinar hosts Eli Stein, Partner and Modern Marketing Capabilities Leader from McKinsey, Ze’ev Rispler, ML Engineer, from Iguazio (acquired by McKinsey), and myself. In 2022, “AI everywhere” has enabled zero marginal cost of content generation. Watch the entire webinar here. This results in money being left on the table.

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DagsHub

DECEMBER 11, 2023

DagsHub DagsHub is a centralized Github-based platform that allows Machine Learning and Data Science teams to build, manage and collaborate on their projects. In addition to versioning code, teams can also version data, models, experiments and more. It does not support the ‘dvc repro’ command to reproduce its data pipeline.

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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. We’ve been running them since 2022. Data Farming (DF) DF is Ocean’s incentives program.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. It has been lightly edited for reading clarity.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. It has been lightly edited for reading clarity.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. It has been lightly edited for reading clarity.

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DagsHub

AUGUST 23, 2024

Even the most sophisticated ML models, neural networks, or large language models require high-quality data to learn meaningful patterns. When bad data is inputted, it inevitably leads to poor outcomes. In 2022, the company ingested bad data from one of its major customers.

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phData

APRIL 18, 2023

Data movements lead to high costs of ETL and rising data management TCO. The inability to access and onboard new datasets prolong the data pipeline’s creation and time to market. Contact phData today for any questions, advice, best practices, or data strategy services.

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Snorkel AI

MAY 12, 2023

Three experts from Capital One ’s data science team spoke as a panel at our Future of Data-Centric AI conference in 2022. Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti.

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Snorkel AI

MAY 12, 2023

Three experts from Capital One ’s data science team spoke as a panel at our Future of Data-Centric AI conference in 2022. Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti.

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Snorkel AI

JULY 3, 2023

Jason Goldfarb, senior data scientist at State Farm , gave a presentation entitled “Reusable Data Cleaning Pipelines in Python” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. It has always amazed me how much time the data cleaning portion of my job takes to complete.

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Snorkel AI

JULY 3, 2023

Jason Goldfarb, senior data scientist at State Farm , gave a presentation entitled “Reusable Data Cleaning Pipelines in Python” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. It has always amazed me how much time the data cleaning portion of my job takes to complete.

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Mlearning.ai

JANUARY 15, 2024

As the order of the variables in the resulting sentence is irrelevant when dealing with tabular data, a random permutation of the components is subsequently performed to improve the final performance of the model. Finally, it is possible to generate new synthetic data from the initial tabular data. Thanks for reading!

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phData

JULY 5, 2024

The release of ChatGPT in late 2022 introduced generative artificial intelligence to the general public and triggered a new wave of AI-oriented companies, products, and open-source projects that provide tools and frameworks to enable enterprise AI.

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phData

JUNE 7, 2023

Data scientists use data-driven approaches to enable AI systems to make better predictions, optimize decision-making, and uncover hidden patterns that ultimately drive innovation and improve performance across various domains. It includes techniques like supervised, unsupervised, and reinforcement learning.

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The MLOps Blog

MAY 9, 2023

One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times.

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AWS Machine Learning Blog

OCTOBER 18, 2023

Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. The solution focuses on the fundamental principles of developing an AI/ML application workflow of data preparation, model training, model evaluation, and model monitoring. DynamoDB is used to store the pet attributes.

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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