DataRobot Blog

AUGUST 16, 2022

The survey asked companies how they used two overlapping types of tools to deploy analytical models: Data operations (DataOps) tools, which focus on creating a manageable, maintainable, automated flow of quality-assured data. Tool adopters are more able to plan their projects, as they are 4.2 Survey Questions. Improving Success.

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AWS Machine Learning Blog

DECEMBER 13, 2023

ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle. Building a robust MLOps pipeline demands cross-functional collaboration. With the right processes and tools, MLOps enables organizations to reliably and efficiently adopt ML across their teams.

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ODSC - Open Data Science

JUNE 7, 2023

Although current explainable AI techniques have made significant progress toward enabling end-users to understand the why behind a prediction, to effectively build trust with an AI system we need to take the next step and make XAI tools interactive. Interactive Explainable AI Meg Kurdziolek, PhD | Staff UX Researcher | Intrinsic.ai

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Explainable AI Responsible AI Data Science Explainability 93

Unite.AI

FEBRUARY 22, 2024

Roadzen has pioneered computer vision research, generative AI and telematics including tools and products for road safety, underwriting and claims. Roadzen's technology stack uses telematics to compile this data, create a comprehensive driver profile, and provide a dynamic quote tailored to each driver.

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AWS Machine Learning Blog

DECEMBER 29, 2022

It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. However, working with data in the cloud can present challenges, such as the need to remove organizational data silos, maintain security and compliance, and reduce complexity by standardizing tooling.

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ODSC - Open Data Science

FEBRUARY 27, 2024

Although current explainable AI techniques have made significant progress toward enabling end-users to understand the why behind a prediction, to effectively build trust with an AI system we need to take the next step and make XAI tools interactive. Interactive Explainable AI Meg Kurdziolek, PhD | Staff UX Researcher | Intrinsic.ai

Explainable AI 52

Explainable AI Responsible AI Data Science Explainability 52

Flipboard

FEBRUARY 15, 2023

JumpStart APIs unlock the usage of JumpStart capabilities in your workflows, and integrate with tools such as the model registry that are part of MLOps pipelines and anywhere else you’re interacting with SageMaker via SDK. In the next section, we demonstrate how you can use SageMaker Pipelines and SageMaker Projects to set up MLOps.

ML 112

ML Natural Language Processing Computer Vision Machine Learning 112

ODSC - Open Data Science

AUGUST 11, 2023

Full-Stack Machine Learning for Data Scientists Hugo Bowne-Anderson, PhD | Head of Data Science Evangelism and Marketing | Outerbounds This workshop will introduce you to the current landscape of production-grade tools, techniques, and workflows for the life cycle of machine learning models.

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Data Scientist Data Science Machine Learning Prompt Engineer 98

ODSC - Open Data Science

FEBRUARY 23, 2023

Solve Your MLOps Problems with an Open Source Data Science Stack These are 10 common problems data scientists face in regard to MLOps alongside some open-source solutions to address them. In the first of two articles, we’d like to share the results, starting with the technical side of things.

Data Science 98

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AWS Machine Learning Blog

APRIL 17, 2023

In conjunction with tools like RStudio on SageMaker, users are analyzing, transforming, and preparing large amounts of data as part of the data science and ML workflow. Create resources with AWS CloudFormation We use an AWS CloudFormation stack to generate the required infrastructure. On the Create stack page, choose Next.

Machine Learning 64

Machine Learning Data Scientist Data Science Natural Language Processing 64

Heartbeat

SEPTEMBER 28, 2023

Project Objective The goal of our project is to predict customer churn for telecommunications companies using a model stacking approach. Model stacking involves training multiple machine learning models and using another model to combine their predictions to improve accuracy. — Credit: KPI Max II. The Project and Dataset 1.

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ODSC - Open Data Science

AUGUST 11, 2023

Orchestrating Data Assets instead of Tasks, with Dagster Sandy Ryza | Lead Engineer — Dagster Project | Elementl Asset-based orchestration works well with modern data stack tools like dbt, Meltano, Airbyte, and Fivetran, because those tools already think in terms of assets.

Data Science 52

Data Science NLP Machine Learning ML 52

ODSC - Open Data Science

OCTOBER 20, 2023

You’ll also learn about the latest tools in NLP, machine learning, MLOps, and more during the Solution Talks. Building and Deploying a Gen AI App in 20 Minutes Nick Schenone | Pre-Sales MLOps Engineer | Iguazio Building your own Generative AI application can be quite difficult. Check them out below.

NLP 52

NLP Data Science Machine Learning Data Analysis 52

AWS Machine Learning Blog

APRIL 22, 2024

You will deploy a CloudFormation stack and create prerequisite resources such as VPC, subnets, security group, and FSx for Lustre volume. You need to create both a primary subnet and backup subnet when deploying the CloudFormation stack, because AWS Managed Microsoft AD requires at least two subnets with different Availability Zones.

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Software Engineer Software Development Machine Learning ML 86

DataRobot Blog

OCTOBER 18, 2022

Knowing this, we walked through a demo of DataRobot AI Cloud MLOps solution , which can manage the open-source models developed by the retailer and regularly provide metrics such as service health, data drift and changes in accuracy. Today, his team is using open-source packages without a standardized AI platform.

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ODSC - Open Data Science

FEBRUARY 13, 2023

The field of data science changes constantly, and some frameworks, tools, and algorithms just can’t get the job done anymore. With ODSC’s Ai+ Live Training platform , you can stay up-to-date with what the leading experts in the field are doing, get hands-on instruction with new tools, and see what the future has in store for the field of AI.

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AWS Machine Learning Blog

MARCH 21, 2023

Therefore, organizations have adopted technology best practices, including microservice architecture, MLOps, DevOps, and more, to improve delivery time, reduce defects, and increase employee productivity. Data Wrangler is a low-code tool that facilitates data analysis, preprocessing, and visualization. Enter a name for Stack name.

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Categorization Python Automation Machine Learning 62

ODSC - Open Data Science

DECEMBER 7, 2023

ML Pros Deep-Dive into Machine Learning Techniques and MLOps Seth Juarez | Principal Program Manager, AI Platform | Microsoft Learn how new, innovative features in Azure machine learning can help you collaborate and streamline the management of thousands of models across teams. Check out a few of the highlights from each group below.

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Data Science Machine Learning Software Architect Algorithm 98

The MLOps Blog

JANUARY 11, 2023

Overall, implementing MLOps in an IoT edge company is important because IoT systems often involve relatively large volumes of data, high levels of complexity, and real-time decision-making. If the machine learning tasks required by your use cases can be implemented using AI services, then you don’t need an MLOps solution.

Machine Learning 52

Machine Learning Automation ML Python 52

ODSC - Open Data Science

AUGUST 24, 2023

The Associated Press and Other News Organizations Develop Standards for AI in the Newsroom This week, the Associated Press along with other news organizations developed standards on how to use AI tools in the newsroom. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Data Science Data Scientist 52

ODSC - Open Data Science

FEBRUARY 22, 2024

Take a deep dive into Machine Learning, NLP, Large Language Models, Generative AI, MLOps, and more with 250+ experts, core contributors, and practitioners shaping the future of AI. Register now for 40% off! Weekly Recap Newsletter Want to get a weekly digest of AI news from around the world every Friday?

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AI Researcher AI Research Large Language Models Machine Learning 52

ODSC - Open Data Science

MARCH 11, 2024

NLP and LLMs The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search.

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AWS Machine Learning Blog

AUGUST 2, 2023

With AI-powered tools and analytics, it has become easier than ever to build not just one story but customized stories to appear to end-users’ unique tastes and sensibilities. Complete the following steps to provision your resources: Choose Launch stack to launch the CloudFormation template in the us-east-1 Region: Choose Next.

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Automation Generative AI Metadata Data Scientist 71

DataRobot Blog

MAY 5, 2022

DataRobot’s already market-leading AutoML, AutoTS, and MLOps products will only be able to drive more value after fully unlocking the power of data-agnostic AI. We make corrections to the model output through Labelbox’s text labeling tool and produce a new training set for DataRobot. Jared Bowns. VP of Engineering at DataRobot.

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ML AI AI Data Scientist 52

AWS Machine Learning Blog

AUGUST 8, 2023

The sparkmagic kernel contains a set of tools for interacting with remote Spark clusters through notebooks. He has worked on projects in different domains, including MLOps, computer vision, and NLP, involving a broad set of AWS services. In his free time, Giuseppe enjoys playing football.

Machine Learning 67

Machine Learning ML Software Engineer Computer Vision 67

ODSC - Open Data Science

MAY 1, 2023

In addition to her role at Microsoft, Eve currently serves on the board of WE Global Studios, a full-stack startup innovation studio supporting female entrepreneurs.` He is also one of the CNCF Working Group Foundation’s first members, and is co-authoring a book on Implementing MLOps in the Enterprise.

Data Science 52

Data Science Machine Learning Big Data Data Scientist 52

Heartbeat

SEPTEMBER 18, 2023

It offers a robust suite of features and tools that facilitate ML workflow productivity, collaboration, and reproducibility. Comet's reputation as a reliable ML platform is built on its ability to integrate with existing infrastructure and tools, providing a unified and efficient environment for ML practitioners.

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ML Data Scientist ML Engineer Machine Learning 52

AWS Machine Learning Blog

APRIL 29, 2024

It provides an approachable, robust Python API for the full infrastructure stack of ML/AI, from data and compute to workflows and observability. We then show how to set up the infrastructure stack you need to take your own data assets and pre-train or fine-tune a state-of-the-art Llama2 model on Trainium hardware. Upload the template.

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ML Python Data Scientist Deep Learning 98

Snorkel AI

JUNE 7, 2023

The pair agreed on the value of the title—noting that it empowered data scientists to focus on a problem and then devise a solution without being anchored to a particular discipline or set of tools. They discussed the impact of open-source models and tools on revolutionizing AI. We are not investing enough. This is a Sputnik moment.

Data Scientist 52

Data Scientist Large Language Models Machine Learning AI 52

Snorkel AI

JUNE 7, 2023

The pair agreed on the value of the title—noting that it empowered data scientists to focus on a problem and then devise a solution without being anchored to a particular discipline or set of tools. They discussed the impact of open-source models and tools on revolutionizing AI. We are not investing enough. This is a Sputnik moment.

Data Scientist 52

Data Scientist Large Language Models Machine Learning AI 52

AWS Machine Learning Blog

MARCH 31, 2023

This will create the Amazon Simple Storage Service (Amazon S3) buckets and roles for the AWS CDK tool to store artifacts and be able to deploy infrastructure. He specializes in Natural Language Processing (NLP), Large Language Models (LLM) and Machine Learning infrastructure and operations projects (MLOps).

IDP 66

IDP Natural Language Processing Machine Learning Software Engineer 66

The MLOps Blog

JANUARY 23, 2023

By now, everyone must have seen THE MLOps paper. Machine Learning Operations (MLOps): Overview, Definition, and Architecture” By Dominik Kreuzberger, Niklas Kühl, Sebastian Hirschl Great stuff. In this article, I share how our reality as the MLOps tooling company and my personal views on MLOps agree (and disagree) with it.

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DevOps Metadata Software Engineer Data Scientist 59

The MLOps Blog

JANUARY 23, 2023

In this article, we will discuss the importance of data versioning control in machine learning and explore various methods and tools for implementing it with different types of data sources. Multiple tools and technologies Machine learning often includes the use of many different tools and technologies. DVC Git LFS neptune.ai

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ML Machine Learning Metadata Data Scientist 52

AWS Machine Learning Blog

NOVEMBER 21, 2023

The second step involves introducing a Transformer-based Spell Correction model in the search stack. To achieve these results, Amazon Music experimented with several different Triton deployment parameters using Triton Model Analyzer , a tool that helps find the best NVIDIA Triton model configuration to deploy efficient inference.

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ML Deep Learning Machine Learning DevOps 81

deepsense.ai

JULY 13, 2023

Integrating these groundbreaking AI tools into your company is not only an investment in the future of technology but will help you pave the way to a smarter, more efficient and customer-driven business. With the rapid expansion of Generative AI, the technology stack behind it also continues to grow with multiple options to choose from.

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Large Language Models LLM ChatGPT Neural Network 80

deepsense.ai

JULY 30, 2023

As a set of concepts, guidelines and tools, LLMOps helps with all of these steps by providing tools and practices that make it easier to manage and maintain a machine learning system. Moreover, however you decide to improve the accuracy of your models, you still need to make sure your system works reliably and consistently.

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Large Language Models LLM Machine Learning Automation 76

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. And later, an MLOps engineer.

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ML Data Scientist Machine Learning Data Science 52