Flipboard

NOVEMBER 24, 2023

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly.

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Dataconomy

APRIL 28, 2025

AWS SageMaker is transforming the way organizations approach machine learning by providing a comprehensive, cloud-based platform that standardizes the entire workflow, from data preparation to model deployment. Data preparation This involves annotating datasets of images and videos for machine learning tasks.

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AWS Machine Learning Machine Learning Data Preparation 91

Flipboard

APRIL 30, 2025

million in seed funding to transform how businesses prepare data for AI, promising to save data scientists from the task that consumes 80% of their time. Brooklyn-based Structify emerges from stealth with $4.1 Read More

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Data Scientist AI AI Data Preparation 165

Dataconomy

MARCH 19, 2025

This structured framework ensures that all necessary stepsfrom data preparation to model monitoringare executed systematically, enhancing efficiency and effectiveness in both business and technology applications. The main components typically include data preparation, model training, deployment, and ongoing monitoring.

Machine Learning 91

Machine Learning Machine Learning Data Preparation ML 91

Dataconomy

MARCH 27, 2023

However, while RPA and ML share some similarities, they differ in functionality, purpose, and the level of human intervention required. In this article, we will explore the similarities and differences between RPA and ML and examine their potential use cases in various industries. What is machine learning (ML)?

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ML ML Machine Learning Machine Learning 133

Towards AI

NOVEMBER 4, 2024

The points to cover in this article are as follows: Generating synthetic data to illustrate ML modelling for election outcomes. Providing some insights into how data scientists might approach real-life election predictions. Model Fitting and Training: Various ML models trained on sub-patterns in data.

Machine Learning 118

Machine Learning Machine Learning Exploratory Data Analysis EDA 118

IBM Data Science in Practice

JANUARY 9, 2024

By Carolyn Saplicki , IBM Data Scientist Industries are constantly seeking innovative solutions to maximize efficiency, minimize downtime, and reduce costs. Many businesses are in different stages of their MAS AI/ML modernization journey. All data scientists could leverage our patterns during an engagement.

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IBM Data Science in Practice

MARCH 21, 2023

This may be a daunting task for a non-data scientist or a data scientist with little to no experience. This article will walk you though how to approach deep learning modeling through the MVI platform from data preparation to your first deployment. What are the types of image processing ML models?

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AWS Machine Learning Blog

FEBRUARY 12, 2024

Sharing in-house resources with other internal teams, the Ranking team machine learning (ML) scientists often encountered long wait times to access resources for model training and experimentation – challenging their ability to rapidly experiment and innovate. If it shows online improvement, it can be deployed to all the users.

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ML ML AWS Machine Learning 138

AWS Machine Learning Blog

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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AWS ML ML Machine Learning 108

AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone makes it straightforward for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization so they can discover, use, and collaborate to derive data-driven insights.

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Machine Learning Machine Learning Data Governance ML 128

phData

NOVEMBER 4, 2024

By providing an integrated environment for data preparation, machine learning, and collaborative analytics, Dataiku empowers teams to harness the full potential of their data without requiring extensive technical expertise. The platform allows data scientists, analysts, and business stakeholders to work together seamlessly.

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Machine Learning Machine Learning Data Science ML 69

AWS Machine Learning Blog

APRIL 26, 2023

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Challenges Customers may face several challenges when implementing machine learning (ML) solutions.

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ML ML AWS Machine Learning 123

AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

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AWS Machine Learning Blog

MARCH 8, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. We add this data to Snowflake as a new table.

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ML ML AWS Python 136

AWS Machine Learning Blog

NOVEMBER 21, 2024

Have an S3 bucket to store your data prepared for batch inference. Have an AWS Identity and Access Management (IAM) role for batch inference with a trust policy and Amazon S3 access (read access to the folder containing input data and write access to the folder storing output data).

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AI AI AWS Data Preparation 118

AWS Machine Learning Blog

JUNE 5, 2025

In this post, we share how Radial optimized the cost and performance of their fraud detection machine learning (ML) applications by modernizing their ML workflow using Amazon SageMaker. Businesses need for fraud detection models ML has proven to be an effective approach in fraud detection compared to traditional approaches.

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Machine Learning Machine Learning AWS ML 59

AWS Machine Learning Blog

MAY 2, 2023

Machine learning (ML) helps organizations generate revenue, reduce costs, mitigate risk, drive efficiencies, and improve quality by optimizing core business functions across multiple business units such as marketing, manufacturing, operations, sales, finance, and customer service.

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ML ML Data Scientist AWS 91

Dataconomy

SEPTEMBER 13, 2023

Data scientists dedicate a significant chunk of their time to data preparation, as revealed by a survey conducted by the data science platform Anaconda. This process involves rectifying or discarding abnormal or non-standard data points and ensuring the accuracy of measurements.

Machine Learning 195

Machine Learning Machine Learning AI AI 195

Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. SageMaker Studio is the first fully integrated development environment (IDE) for ML. You can use query_string to filter your dataset by SQL and unload it to Amazon S3.

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ML ML AWS Data Warehouse 123

AWS Machine Learning Blog

DECEMBER 1, 2023

The ability to quickly build and deploy machine learning (ML) models is becoming increasingly important in today’s data-driven world. However, building ML models requires significant time, effort, and specialized expertise. And experienced data scientists can be hard to come by.

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Machine Learning Machine Learning Data Preparation ML 124

AWS Machine Learning Blog

MARCH 22, 2023

You can use machine learning (ML) to generate these insights and build predictive models. Educators can also use ML to identify challenges in learning outcomes, increase success and retention among students, and broaden the reach and impact of online learning content. Import the Dropout_Academic Success - Sheet1.csv

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Machine Learning Machine Learning Data Scientist ML 96

Iguazio

JUNE 5, 2025

adds features to make LLM and ML evaluation and monitoring more accessible, practical and resource-efficient. These capabilities include LLM monitoring, fine-tuning, data management, built-in guardrails and more. further enhances LLM and ML model monitoring capabilities across the lifecycle. On the heels of MLRun v1.7

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AWS Machine Learning Blog

AUGUST 3, 2023

As machine learning (ML) becomes increasingly prevalent in a wide range of industries, organizations are finding the need to train and serve large numbers of ML models to meet the diverse needs of their customers. Here, the checkpoints need to be saved in a pre-specified location, with the default being /opt/ml/checkpoints.

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ML ML AWS Python 97

Data Science Dojo

AUGUST 28, 2023

Similar to traditional Machine Learning Ops (MLOps), LLMOps necessitates a collaborative effort involving data scientists, DevOps engineers, and IT professionals. Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Machine learning operations (MLOps) are a set of practices that automate and simplify machine learning (ML) workflows and deployments. AWS published Guidance for Optimizing MLOps for Sustainability on AWS to help customers maximize utilization and minimize waste in their ML workloads.

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AWS Data Preparation ML ML 117

Towards AI

JUNE 27, 2023

Let’s get started with the best machine learning (ML) developer tools: TensorFlow TensorFlow, developed by the Google Brain team, is one of the most utilized machine learning tools in the industry. Scikit Learn Scikit Learn is a comprehensive machine learning tool designed for data mining and large-scale unstructured data analysis.

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Machine Learning Machine Learning ML ML 98

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Launched in 2021, Amazon SageMaker Canvas is a visual point-and-click service that allows business analysts and citizen data scientists to use ready-to-use machine learning (ML) models and build custom ML models to generate accurate predictions without writing any code.

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AWS Machine Learning Blog

APRIL 3, 2024

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. SageMaker Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity.

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Machine Learning Machine Learning ML ML 133

AWS Machine Learning Blog

NOVEMBER 15, 2024

jpg", "prompt": "Which part of Virginia is this letter sent from", "completion": "Richmond"} SageMaker JumpStart SageMaker JumpStart is a powerful feature within the SageMaker machine learning (ML) environment that provides ML practitioners a comprehensive hub of publicly available and proprietary foundation models (FMs).

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment.

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AWS Machine Learning Machine Learning ML 128

Heartbeat

FEBRUARY 1, 2023

Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. They might also help with data preparation and cleaning.

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Machine Learning Machine Learning Data Scientist ML 96

AWS Machine Learning Blog

FEBRUARY 6, 2024

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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AWS Machine Learning Blog

OCTOBER 5, 2023

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption across enterprise and government organizations. Processing unstructured data has become easier with the advancements in natural language processing (NLP) and user-friendly AI/ML services like Amazon Textract , Amazon Transcribe , and Amazon Comprehend.

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How to Learn Machine Learning

APRIL 26, 2025

The field of data science is now one of the most preferred and lucrative career options available in the area of data because of the increasing dependence on data for decision-making in businesses, which makes the demand for data science hires peak. And Why did it happen?). or What might be the best course of action?

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

AWS Machine Learning Blog

JANUARY 6, 2023

The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning (ML) model development, including data preparation, model building and training, model operation, evaluation, deployment, and monitoring. AI life-cycle tools are essential to productize AI/ML solutions.

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AWS ML ML Data Preparation 94

Dataconomy

MARCH 27, 2023

However, while RPA and ML share some similarities, they differ in functionality, purpose, and the level of human intervention required. In this article, we will explore the similarities and differences between RPA and ML and examine their potential use cases in various industries. What is machine learning (ML)?

ML 70

ML ML Machine Learning Machine Learning 70