Flipboard

MAY 9, 2025

client('bedrock-runtime') def analyze_sentiment(text, model_id= {selected_model}): # Construct the prompt prompt = f"""You are an expert AI sentiment analyst with advanced natural language processing capabilities. He is focused on big data, data lakes, streaming and batch analytics services, and generative AI technologies.

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AWS Natural Language Processing AI AI 93

Dataversity

FEBRUARY 24, 2021

The amount of data generated in the digital world is increasing by the minute! This massive amount of data is termed “big data.” We may classify the data as structured, unstructured, or semi-structured. Data that is structured or semi-structured is relatively easy to store, process, and analyze. […].

Big Data 59

Big Data Big Data Natural Language Processing Data Lakes 59

ODSC - Open Data Science

DECEMBER 19, 2023

Data Engineer Data engineers are responsible for the end-to-end process of collecting, storing, and processing data. They use their knowledge of data warehousing, data lakes, and big data technologies to build and maintain data pipelines.

Data Scientist 96

Data Scientist Machine Learning Machine Learning Computer Science 96

AWS Machine Learning Blog

AUGUST 2, 2024

He has more than 8 years of experience with big data and machine learning projects in financial, retail, energy, and chemical industries. His main interests include natural language processing and generative AI. Outside of work, he is a travel enthusiast. Guillermo Menéndez Corral is a Sr.

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AWS Machine Learning Machine Learning Database 123

AWS Machine Learning Blog

APRIL 30, 2025

ENGIEs One Data team partnered with AWS Professional Services to develop an AI-powered chatbot that enables natural language conversation search within ENGIEs Common Data Hub data lake, over 3 petabytes of data. Daniel Zagyva is a Senior ML Engineer at AWS Professional Services.

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AWS AI AI Machine Learning 66

AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL.

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SQL AWS Database ML 139

DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Tools like Unstructured.io

AI 52

AI AI Data Lakes Database 52

ODSC - Open Data Science

MARCH 11, 2024

Data Morph: A Cautionary Tale of Summary Statistics Visualization in Bayesian Workflow Using Python or R Harnessing Bayesian Statistics for Business-Centric Data Science Data Engineering and Big Data Join this track to learn the latest techniques and processes to analyze raw data and automate data into mechanical processes and algorithms.

Data Science 52

Data Science Deep Learning Deep Learning Machine Learning 52

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

DagsHub

OCTOBER 23, 2024

To combine the collected data, you can integrate different data producers into a data lake as a repository. A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Data Cleaning The next step is to clean the data after ingesting it into the data lake.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

AWS Machine Learning Blog

AUGUST 2, 2023

The process is also known as image captioning , and operates at the intersection of computer vision and natural language processing (NLP). Marketing firms store vast amounts of digital data that needs to be centralized, easily searchable, and scalable enabled by data catalogs.

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AWS AI AI Machine Learning 94

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. This is especially helpful when handling massive amounts of big data.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Pickl AI

MARCH 10, 2025

Impact: Scales seamlessly as organisational data grows. AI-Powered Insights Power BI incorporates Artificial Intelligence (AI) capabilities for advanced analytics like Natural Language Processing (NLP), image recognition, and machine learning model integration. Is Power BI Suitable for Small Businesses?

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Power BI Business Intelligence Business Intelligence Analytics 52

Pickl AI

SEPTEMBER 5, 2024

Storage Solutions: Secure and scalable storage options like Azure Blob Storage and Azure Data Lake Storage. Key features and benefits of Azure for Data Science include: Scalability: Easily scale resources up or down based on demand, ideal for handling large datasets and complex computations.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

IBM Journey to AI blog

OCTOBER 16, 2023

Voice-based queries use Natural Language Processing (NLP) and sentiment analysis for speech recognition. ML also helps businesses forecast and decrease customer churn (the rate at which a company loses customers), a widespread use of big data. The platform has three powerful components: the watsonx.ai

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

JANUARY 26, 2024

Also consider using Amazon Security Lake to automatically centralize security data from AWS environments, SaaS providers, on premises, and cloud sources into a purpose-built data lake stored in your account. Emily Soward is a Data Scientist with AWS Professional Services.

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AWS ML ML AI 137

Flipboard

JUNE 16, 2025

Amazon Comprehend is a natural language processing and machine learning service capable of extracting metadata, extracting key phrases and determining sentiment from text in multiple languages. The natural evolution for a data market like this is the arrival of industry-specific services aligned to industry verticals.

Big Data 134

Big Data Big Data Machine Learning Machine Learning 134