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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Mlearning.ai

JUNE 16, 2023

Increase your productivity in software development with Generative AI As I mentioned in Generative AI use case article, we are seeing AI-assisted developers. Overall Generative AI in SDLC Here is how Generative AI can help in SDLC stages (we may see more use cases as Generative AI matures).

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The MLOps Blog

NOVEMBER 30, 2022

Data science teams currently struggle with managing multiple experiments and models and need an efficient way to store, retrieve, and utilize details like model versions, hyperparameters, and performance metrics. ML model versioning: where are we at? The short answer is we are in the middle of a data revolution.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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DagsHub

APRIL 21, 2024

Source: [link] Similarly, while building any machine learning-based product or service, training and evaluating the model on a few real-world samples does not necessarily mean the end of your responsibilities. You need to make that model available to the end users, monitor it, and retrain it for better performance if needed.

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Snorkel AI

JUNE 7, 2023

Snorkel AI hosted the first day of the two-day The Future of Data-Centric AI virtual conference today, featuring Matei Zaharia, the creator of Spark, DJ Patil, the first U.S. Chief Data Scientist, and other esteemed speakers and panelists. The output of generative models defies simple comparisons to test sets.

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Snorkel AI

JUNE 7, 2023

Snorkel AI hosted the first day of the two-day The Future of Data-Centric AI virtual conference today, featuring Matei Zaharia, the creator of Spark, DJ Patil, the first U.S. Chief Data Scientist, and other esteemed speakers and panelists. The output of generative models defies simple comparisons to test sets.

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O'Reilly Media

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. What does a modern technology stack for streamlined ML processes look like? Why: Data Makes It Different. All ML projects are software projects.

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Mlearning.ai

SEPTEMBER 4, 2023

Turbo model, this may be a better fit for some businesses.[2],[3] 2],[3] It’s important to note that even with a million-dollar investment, it may be challenging to match the general performance and latency of these commercial models.[4] 4] Private instances: Microsoft Azure provides a private instance of ChatGPT.

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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. DVC can efficiently handle large files and machine learning models.

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ODSC - Open Data Science

APRIL 6, 2023

But its status as the go-between for programming and data professionals isn’t its only power. Within SQL you can also filter data, aggregate it and create valuations, manipulate data, update it, and even do data modeling. Finally, cloud services.

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The MLOps Blog

JANUARY 25, 2023

ML-Based Approach: Rule-based approach fails to identify things like Irony and sarcasm, multiple types of negations, word ambiguity, and multipolarity in text. Due to this, businesses are now focusing on an ML-based approach, where different ML algorithms are trained on a large dataset of prelabeled text.

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phData

JULY 18, 2023

The good news is that there’s a concept called the Modern Data Stack that when utilized properly, consistently helps empower organizations to harness the full potential of their data. Throughout this journey, we’ve helped hundreds of clients achieve eye-opening results by moving to the Modern Data Stack.

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