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 165

Python Natural Language Processing Data Science Machine Learning 165

Towards AI

JULY 1, 2024

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. The whole thing is very exciting, but where do I get the data from?

ETL 85

ETL Data Scientist Data Engineer Data Engineering 85

Data Science Dojo

FEBRUARY 20, 2023

These tools will help you streamline your machine learning workflow, reduce operational overheads, and improve team collaboration and communication. Machine learning (ML) is the technology that automates tasks and provides insights. It allows data scientists to build models that can automate specific tasks.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Towards AI

MARCH 21, 2023

Navigating the World of Data Engineering: A Beginner’s Guide. A GLIMPSE OF DATA ENGINEERING ❤ IMAGE SOURCE: BY AUTHOR Data or data? No matter how you read or pronounce it, data always tells you a story directly or indirectly. Data engineering can be interpreted as learning the moral of the story.

Data Engineering 95

Data Engineering Data Engineering Data Engineering Data Engineer 95

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

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 Engineering Data Engineering Data Engineer 52

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

Flipboard

DECEMBER 18, 2023

Customers use Amazon Redshift as a key component of their data architecture to drive use cases from typical dashboarding to self-service analytics, real-time analytics, machine learning (ML), data sharing and monetization, and more.

AWS 139

AWS Data Warehouse ETL SQL 139

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

The MLOps Blog

MAY 17, 2023

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

ETL 59

ETL Data Pipeline ML ML 59

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

AWS Machine Learning Blog

FEBRUARY 21, 2025

He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations. Chaithanya Maisagoni is a Senior Software Development Engineer (AI/ML) in Amazons Worldwide Returns and ReCommerce organization.

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AWS Natural Language Processing Machine Learning Machine Learning 129

The MLOps Blog

SEPTEMBER 7, 2023

Data Scientists and ML Engineers typically write lots and lots of code. From writing code for doing exploratory analysis, experimentation code for modeling, ETLs for creating training datasets, Airflow (or similar) code to generate DAGs, REST APIs, streaming jobs, monitoring jobs, etc. risk models vs. recommender systems).

Machine Learning 52

Machine Learning Machine Learning ETL ML 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 Engineering Data Engineering Data Engineer 52

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

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

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 Engineering Data Engineering Data Engineer 52

Applied Data Science

AUGUST 2, 2021

Machine learning The 6 key trends you need to know in 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 Data Engineer Not everyone working on a data science project is a data scientist.

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Data Science Data Scientist ML ML 130

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 Engineering 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 Engineering Data Engineering Data Engineer 52

AWS Machine Learning Blog

NOVEMBER 20, 2024

She has experience across analytics, big data, ETL, cloud operations, and cloud infrastructure management. Data Engineer at Amazon Ads. He builds and manages data-driven solutions for recommendation systems, working together with a diverse and talented team of scientists, engineers, and product managers.

Database 116

Database AWS SQL ETL 116

Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Zeta’s AI innovation is powered by a proprietary machine learning operations (MLOps) system, developed in-house. Context In early 2023, Zeta’s machine learning (ML) teams shifted from traditional vertical teams to a more dynamic horizontal structure, introducing the concept of pods comprising diverse skill sets.

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AWS Machine Learning Machine Learning ML 127

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 Engineering Data Engineer 52

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. This post is co-written with Jayadeep Pabbisetty, Sr.

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ML ML AWS Machine Learning 134

AWS Machine Learning Blog

FEBRUARY 21, 2025

Data exploration and model development were conducted using well-known machine learning (ML) tools such as Jupyter or Apache Zeppelin notebooks. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. Analytic data is stored in Amazon Redshift.

Data Science 84

Data Science AWS Hadoop Data Scientist 84

Towards AI

JANUARY 28, 2024

To start, get to know some key terms from the demo: Snowflake: The centralized source of truth for our initial data Magic ETL: Domo’s tool for combining and preparing data tables ERP: A supplemental data source from Salesforce Geographic: A supplemental data source (i.e., Instagram) used in the demo Why Snowflake?

ETL 110

ETL Python Database Data Preparation 110

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 Engineering Data Engineer 52

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 Quality Data Pipeline Data Warehouse 40

AWS Machine Learning Blog

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required. To learn more, see the documentation.

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AWS ML ML Data Quality 98

Women in Big Data

OCTOBER 9, 2024

Big data management involves a series of processes, including collecting, cleaning, and standardizing data for analysis, while continuously accommodating new data streams. These procedures are central to effective data management and crucial for deploying machine learning models and making data-driven decisions.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

DagsHub

OCTOBER 23, 2024

Unstructured data makes up 80% of the world's data and is growing. Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. Unstructured.io

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

AWS Machine Learning Blog

JANUARY 5, 2024

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. Scaling is one of the biggest issues in the machine learning cycle.

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AWS Data Science ML ML 137

AWS Machine Learning Blog

JUNE 18, 2024

More than 170 tech teams used the latest cloud, machine learning and artificial intelligence technologies to build 33 solutions. LLMs excel at writing code and reasoning over text, but tend to not perform as well when interacting directly with time-series data.

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AWS Python AI AI 135

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. Big Data Architect. Zach Mitchell is a Sr.

SQL 160

SQL AWS Data Lakes AI 160

Becoming Human

JANUARY 23, 2023

Just like this in Data Science we have Data Analysis , Business Intelligence , Databases , Machine Learning , Deep Learning , Computer Vision , NLP Models , Data Architecture , Cloud & many things, and the combination of these technologies is called Data Science. Data Science and AI are related?

Data Science 105

Data Science Big Data Big Data Deep Learning 105

IBM Journey to AI blog

MARCH 14, 2024

Db2 Warehouse fully supports open formats such as Parquet, Avro, ORC and Iceberg table format to share data and extract new insights across teams without duplication or additional extract, transform, load (ETL). This allows you to scale all analytics and AI workloads across the enterprise with trusted data. 

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AWS Database ETL AI 93