Flipboard

JANUARY 6, 2025

The federal government agency Precise worked with needed to automate manual processes for document intake and image processing. The agency wanted to use AI [artificial intelligence] and ML to automate document digitization, and it also needed help understanding each document it digitizes, says Duan.

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AWS ML ML Machine Learning 65

Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. Data Analysis and Report AI The GPT uses AI tools for data analysis and report generation.

Data Science 363

Data Science Data Analysis Data Analysis Machine Learning 363

Data Science Dojo

SEPTEMBER 10, 2024

LLM companies are businesses that specialize in developing and deploying Large Language Models (LLMs) and advanced machine learning (ML) models. It has also risen as a dominant player in the LLM space, leading the changes within the landscape of natural language processing and AI-driven solutions.

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Machine Learning Machine Learning Natural Language Processing ML 369

Data Science Dojo

MARCH 8, 2024

It also facilitates integration with different applications to enhance their functionality with organized access to data. In data science, databases are important for data preprocessing, cleaning, and integration. Data scientists often rely on databases to perform complex queries and visualize data.

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Database Natural Language Processing Clustering SQL 370

Dataconomy

MARCH 27, 2023

Both have the potential to transform the way organizations operate, enabling them to streamline processes, improve efficiency, and drive business outcomes. However, while RPA and ML share some similarities, they differ in functionality, purpose, and the level of human intervention required. What is machine learning (ML)?

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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 137

AWS Machine Learning Blog

NOVEMBER 29, 2024

22.03% The consistent improvements across different tasks highlight the robustness and effectiveness of Prompt Optimization in enhancing prompt performance for various natural language processing (NLP) tasks. Chris Pecora is a Generative AI Data Scientist at Amazon Web Services.

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Data Science Dojo

OCTOBER 27, 2023

Data Science Dojo Large Language Models Bootcamp The Data Science Dojo Large Language Models Bootcamp is a 5-day in-person bootcamp that teaches you everything you need to know about large language models (LLMs) and their real-world applications. Who should attend?

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AWS Machine Learning Blog

AUGUST 12, 2024

Instead, organizations are increasingly looking to take advantage of transformative technologies like machine learning (ML) and artificial intelligence (AI) to deliver innovative products, improve outcomes, and gain operational efficiencies at scale. Data is presented to the personas that need access using a unified interface.

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AWS Machine Learning Blog

JANUARY 22, 2025

Converting free text to a structured query of event and time filters is a complex natural language processing (NLP) task that can be accomplished using FMs. Daniel Pienica is a Data Scientist at Cato Networks with a strong passion for large language models (LLMs) and machine learning (ML).

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Natural Language Processing Machine Learning Machine Learning ML 115

Flipboard

DECEMBER 3, 2024

As a global leader in agriculture, Syngenta has led the charge in using data science and machine learning (ML) to elevate customer experiences with an unwavering commitment to innovation. Zach is dedicated to exploring innovative ways to enhance farming efficiency and sustainability through AI and data-driven approaches.

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AWS AI AI Machine Learning 149

AWS Machine Learning Blog

OCTOBER 29, 2024

Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. With a strong background in AI/ML, Ishan specializes in building Generative AI solutions that drive business value.

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AWS AI AI Data Scientist 117

AWS Machine Learning Blog

JANUARY 29, 2025

Raj specializes in Machine Learning with applications in Generative AI, Natural Language Processing, Intelligent Document Processing, and MLOps. Ishan Singh is a Generative AI Data Scientist at Amazon Web Services, where he helps customers build innovative and responsible generative AI solutions and products.

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Data Science Dojo

AUGUST 6, 2024

These algorithms significantly enhance accuracy, reduce bias, and effectively handle complex data patterns. Their ability to uncover feature importance makes them valuable tools for various ML tasks, including classification, regression, and ranking problems.

Machine Learning 195

Machine Learning Machine Learning Algorithm ML 195

Dataconomy

MAY 2, 2023

The machine learning systems developed by Machine Learning Engineers are crucial components used across various big data jobs in the data processing pipeline. Additionally, Machine Learning Engineers are proficient in implementing AI or ML algorithms. Is ML engineering a stressful job?

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ML ML Machine Learning Machine Learning 110

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. To start our ML project predicting the probability of readmission for diabetes patients, you need to download the Diabetes 130-US hospitals dataset.

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ML ML AWS Data Scientist 93

Google Research AI blog

MARCH 30, 2023

Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. Each step can introduce issues and biases.

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Flipboard

JUNE 3, 2025

Approval workflows streamline model training and deployment processes, and AWS cross-account deployment enables resource allocation across organizational boundaries. The framework uses templates with Hugging Face text classification models, enabling rapid deployment of natural language processing capabilities.

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Machine Learning Machine Learning AWS Data Scientist 73

Data Science Connect

JULY 24, 2023

In the rapidly evolving world of data science, where cutting-edge technology drives innovation, the traditional one-size-fits-all software solutions are increasingly being challenged. Micro-SaaS , short for Micro Software-as-a-Service, is gaining traction as an innovative approach to solving complex data science problems.

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Data Science Citizen Data Scientist Data Scientist ML 100

Towards AI

MAY 3, 2023

They investigate the most suitable algorithms, identify the best weights and hyperparameters, and might even collaborate with fellow data scientists in the community to develop an effective strategy. This is where ML CoPilot enters the scene. Vector databases can store them and are designed for search and data mining.

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ML ML Machine Learning Machine Learning 96

Towards AI

JUNE 27, 2023

For instance, today’s machine learning tools are pushing the boundaries of natural language processing, allowing AI to comprehend complex patterns and languages. 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 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. SageMaker Studio set up.

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ML ML AWS SQL 129

Applied Data Science

AUGUST 2, 2021

With a range of role types available, how do you find the perfect balance of Data Scientists , Data Engineers and Data Analysts to include in your team? The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data.

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Data Science Data Scientist ML ML 130

Data Science Dojo

APRIL 16, 2024

Machine learning (ML) engineer Potential pay range – US$82,000 to 160,000/yr Machine learning engineers are the bridge between data science and engineering. Integrating the knowledge of data science with engineering skills, they can design, build, and deploy machine learning (ML) models.

AI 195

AI AI Machine Learning Machine Learning 195

Data Science Dojo

JANUARY 13, 2023

The conference features a wide range of topics within AI, including machine learning, natural language processing, computer vision, and robotics, as well as interdisciplinary areas such as AI and law, AI and education, and AI and the arts. It also includes tutorials, workshops, and invited talks by leading experts in the field.

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AWS Machine Learning Blog

MAY 15, 2025

This substantial reduction in processing time not only accelerates workflows but also minimizes the risk of manual errors. To further enhance the capabilities of specialized information extraction solutions, advanced ML infrastructure is essential. Creating robust ML models is challenging due to the scarcity of clean training data.

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AWS ML ML Machine Learning 92

Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. This integration combines visual features extracted from images with language models to generate descriptive and contextually relevant captions.

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

SageMaker Studio is an integrated development environment (IDE) for machine learning (ML). ML practitioners can perform all ML development steps—from preparing their data to building, training, and deploying ML models—within a single, integrated visual interface.

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AWS ML ML Machine Learning 121

AWS Machine Learning Blog

FEBRUARY 12, 2025

Large language models (LLMs) have revolutionized the field of natural language processing with their ability to understand and generate humanlike text. This blog post is co-written with Moran beladev, Manos Stergiadis, and Ilya Gusev from Booking.com.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

SageMaker endpoints can be registered to the Salesforce Data Cloud to activate predictions in Salesforce. SageMaker Canvas also enables you to understand your predictions using feature importance and SHAP values, making it straightforward for you to explain predictions made by ML models.

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ML ML AWS SQL 108

AWS Machine Learning Blog

MAY 28, 2025

With this launch, developers and data scientists can now deploy Gemma 3, a 27-billion-parameter language model, along with its specialized instruction-following versions, to help accelerate building, experimentation, and scalable deployment of generative AI solutions on AWS. Pawan Matta is a Sr. Solutions Architect at AWS.

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AWS Machine Learning Blog

AUGUST 5, 2024

The solution simplifies the setup process, allowing you to quickly deploy and start querying your data using the selected FM. About the Authors Sandeep Singh is a Senior Generative AI Data Scientist at Amazon Web Services, helping businesses innovate with generative AI. Please share your feedback to us!

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AWS Machine Learning Blog

MARCH 21, 2025

In addition to Anthropics Claude on Amazon Bedrock, the solution uses the following services: Amazon SageMaker JupyterLab The SageMakerJupyterLab application is a web-based interactive development environment (IDE) for notebooks, code, and data. We use JupyterLab to run the code for processing formulae and charts.

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AWS AI AI Data Scientist 117

Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. Data Analysis and Report AI The GPT uses AI tools for data analysis and report generation.

Data Science 195

Data Science Data Analysis Data Analysis Machine Learning 195

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).

ML 112

ML ML Python AWS 112

Data Science Dojo

FEBRUARY 23, 2024

Data Analysis and Report AI The data science GPT uses AI tools for data analysis and report generation. It uses machine learning and natural language processing for automation and enhancement of data analytical processes. You cannot use a GPT focused on healthcare within the field of finance.

Data Science 195

Data Science Data Analysis Data Analysis Data Analyst 195

AWS Machine Learning Blog

JUNE 23, 2023

For data scientists, moving machine learning (ML) models from proof of concept to production often presents a significant challenge. It can be cumbersome to manage the process, but with the right tool, you can significantly reduce the required effort. From / , you could run the API and get the “hello world” message.

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AWS ML ML Python 102