KDnuggets

JUNE 9, 2025

His vision is to build an AI product using a graph neural network for students struggling with mental illness.

Natural Language Processing 301

Natural Language Processing Data Science Machine Learning Machine Learning 301

databricks

JUNE 4, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

AWS 130

AWS AI AI Data Science 130

Data Science Dojo

OCTOBER 31, 2024

Research Data Scientist Description : Research Data Scientists are responsible for creating and testing experimental models and algorithms. According to Google AI, they work on projects that may not have immediate commercial applications but push the boundaries of AI research.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

KDnuggets

JUNE 6, 2025

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 5 Error Handling Patterns in Python (Beyond Try-Except) Stop letting errors crash your app.

Python 221

Python Natural Language Processing Data Science Machine Learning 221

Towards AI

JULY 1, 2024

Last Updated on July 3, 2024 by Editorial Team Author(s): Marcello Politi Originally published on Towards AI. Learn the basics of data engineering to improve your ML modelsPhoto by Mike Benna on Unsplash It is not news that developing Machine Learning algorithms requires data, often a lot of data.

ETL 96

ETL Data Scientist Data Engineering Data Engineer 96

Towards AI

MARCH 21, 2023

Last Updated on March 21, 2023 by Editorial Team Author(s): Data Science meets Cyber Security Originally published on Towards AI. Navigating the World of Data Engineering: A Beginner’s Guide. A GLIMPSE OF DATA ENGINEERING ❤ IMAGE SOURCE: BY AUTHOR Data or data? What are ETL and data pipelines?

Data Engineering 98

Data Engineering Data Engineering Data Engineer Data Engineering 98

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Flipboard

JULY 3, 2025

Although rapid generative AI advancements are revolutionizing organizational natural language processing tasks, developers and data scientists face significant challenges customizing these large models. Model development capabilities from SageMaker AI are available within SageMaker Unified Studio.

ML 91

ML AWS ML Data Engineering 91

Hacker News

NOVEMBER 19, 2024

About the Role TigerEye is an AI Analyst for everyone in go-to-market. We track the changes in a company’s business to deliver instant, accurate answers to complex questions through a simple app.

Computer Science 150

Computer Science Computer Science ETL ML 150

IBM Journey to AI blog

MAY 15, 2024

Business leaders risk compromising their competitive edge if they do not proactively implement generative AI (gen AI). However, businesses scaling AI face entry barriers. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

Data Pipeline 85

Data Pipeline ETL SQL Database 85

Dataconomy

JUNE 23, 2025

Team structure in DataOps Effective DataOps teams consist of various roles that contribute to a seamless data lifecycle. Leadership often includes a Chief Data Scientist or Chief Analytics Officer who guides the strategy and vision. Collaboratively, team members such as: Data engineers: Who design and maintain data pipelines.

DataOps 91

DataOps Data Pipeline Data Quality Data Science 91

AWS Machine Learning Blog

JULY 3, 2025

This challenge led Swisscom , Switzerland’s leading telecommunications provider, to explore how AI can transform their network operations. This solution combines generative AI capabilities with a sophisticated data processing pipeline to help engineers quickly access and analyze network data.

AWS 72

AWS AI AI SQL 72

ODSC - Open Data Science

MARCH 20, 2025

30% Off ODSC East, Fan-Favorite Speakers, Foundation Models for Times Series, and ETL Pipeline Orchestration The ODSC East 2025 Schedule isLIVE! Explore the must-attend sessions and cutting-edge tracks designed to equip AI practitioners, data scientists, and engineers with the latest advancements in AI and machine learning.

ETL 52

ETL Data Science Machine Learning Machine Learning 52

ODSC - Open Data Science

JULY 4, 2025

From October 28–30 in San Francisco, ODSC West 2025 returns with a robust lineup of 15 tracks aimed at helping professionals build practical skills and stay ahead of emerging trends in AI. Learn how to build resilient, production-grade AI systems end-to-end. Ideal for building robust NLP applications and production pipelines.

Deep Learning 52

Deep Learning Deep Learning ML ML 52

ODSC - Open Data Science

FEBRUARY 19, 2025

In the world of AI-driven data workflows, Brij Kishore Pandey, a Principal Engineer at ADP and a respected LinkedIn influencer, is at the forefront of integrating multi-agent systems with Generative AI for ETL pipeline orchestration. ETL ProcessBasics So what exactly is ETL?

ETL 52

ETL AI AI Data Warehouse 52

Pickl AI

APRIL 9, 2025

Summary: This guide explores the top list of ETL tools, highlighting their features and use cases. It provides insights into considerations for choosing the right tool, ensuring businesses can optimize their data integration processes for better analytics and decision-making. What is ETL? What are ETL Tools?

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Pickl AI

OCTOBER 17, 2024

Summary: This article explores the significance of ETL Data in Data Management. It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Flipboard

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

AWS 130

AWS Data Warehouse ETL SQL 130

Towards AI

JANUARY 28, 2024

Last Updated on January 29, 2024 by Editorial Team Author(s): Cassidy Hilton Originally published on Towards AI. Recapping the Cloud Amplifier and Snowflake Demo The combined power of Snowflake and Domo’s Cloud Amplifier is the best-kept secret in data management right now — and we’re reaching new heights every day.

ETL 111

ETL Python Database Data Preparation 111

Data Science Dojo

FEBRUARY 20, 2023

It is used by businesses across industries for a wide range of applications, including fraud prevention, marketing automation, customer service, artificial intelligence (AI), chatbots, virtual assistants, and recommendations. we have Databricks which is an open-source, next-generation data management platform.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

AWS Machine Learning Blog

FEBRUARY 21, 2025

With the current housing shortage and affordability concerns, Rocket simplifies the homeownership process through an intuitive and AI-driven experience. One such opportunity is using data science solutions, but to do so, we must have a strong and flexible data science environment.

Data Science 90

Data Science AWS Hadoop Data Scientist 90

Applied Data Science

AUGUST 2, 2021

This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI  — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data.

Data Science 130

Data Science Data Scientist Data Analyst Machine Learning 130

Hacker News

JULY 18, 2024

ABOUT EVENTUAL Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI. OUR PRODUCT IS OPEN-SOURCE AND USED AT ENTERPRISE SCALE Our distributed data engine Daft [link] is open-sourced and runs on 800k CPU cores daily.

ML 127

ML ML Python ETL 127

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

JANUARY 18, 2024

Data engineering is a rapidly growing field, and there is a high demand for skilled data engineers. If you are a data scientist, you may be wondering if you can transition into data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

JULY 8, 2023

In this article we’re going to check what is an Azure function and how we can employ it to create a basic extract, transform and load (ETL) pipeline with minimal code. Extract, transform and Load Before we begin, let’s shed some light on what an ETL pipeline essentially is. ELT stands for extract, load and transform.

ETL 52

ETL Azure Python Internet of Things 52

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

NOVEMBER 20, 2024

Whether it’s structured data in databases or unstructured content in document repositories, enterprises often struggle to efficiently query and use this wealth of information. The solution combines data from an Amazon Aurora MySQL-Compatible Edition database and data stored in an Amazon Simple Storage Service (Amazon S3) bucket.

Database 113

Database AWS SQL ETL 113

ODSC - Open Data Science

MARCH 12, 2025

The Rise of AI Engineering andMLOps 20182019: Early discussions around MLOps and AI engineering were sparse, primarily focused on general machine learning best practices. 20232024: AI engineering became a hot topic, expanding beyond MLOps to include AI agents, autonomous systems, and scalable model deployment techniques.

Data Science 52

Data Science Machine Learning Machine Learning Data Engineering 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

Whether youre new to AI development or an experienced practitioner, this post provides step-by-step guidance and code examples to help you build more reliable AI applications. Chaithanya Maisagoni is a Senior Software Development Engineer (AI/ML) in Amazons Worldwide Returns and ReCommerce organization.

AWS 127

AWS Natural Language Processing Machine Learning Machine Learning 127

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. Their insights must be in line with real-world goals.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

JANUARY 11, 2024

Getting Started with AI in High-Risk Industries, How to Become a Data Engineer, and Query-Driven Data Modeling How To Get Started With Building AI in High-Risk Industries This guide will get you started building AI in your organization with ease, axing unnecessary jargon and fluff, so you can start today.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. The following screenshot illustrates the SageMaker Unified Studio.

SQL 137

SQL AWS Data Lakes ML 137

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS 93

AWS Database ETL AI 93

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

ETL 40

ETL Data Pipeline Data Quality Hadoop 40