Sat.Mar 22, 2025 - Fri.Mar 28, 2025

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10 Pandas One-Liners for Data Cleaning

KDnuggets

Want to make data cleaning more enjoyable? These pandas one-liners for data cleaning will help you get more done with less!

Data 103
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What Is Data Imputation: Purpose, Techniques, & Methods

Edureka

Imputation in statistics means replacing missing data with different numbers. “Unit imputation” means replacing a whole data point, while “item imputation” means replacing part of a data point. Missing information can cause bias, make data analysis harder, and lower efficiency. These are the three main problems it creates. Imputation is a way to handle missing data instead of simply removing cases with missing values, as missing information can make data analysis more dif

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AI in Education: Transforming Learning in the Digital Age

WeCloudData

Artificial intelligence (AI) is no longer a futuristic concept, but a powerful tool reshaping education, offering personalized learning and improved outcomes. This aligns perfectly with the Education 4.0 Framework, which aims to transform education for the Fourth Industrial Revolution. By strategically implementing AI, we can directly contribute to realizing this vision, ensuring learners are prepared […] The post AI in Education: Transforming Learning in the Digital Age appeared first on

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A Solutions Engineer's Take on How to Empower Customers

Confluent

Learn how Confluent Champion Syed solves complex problems for customersand how Confluent's collaborative culture keeps him motivated.

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The Ultimate Guide to Apache Airflow DAGS

With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you

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Building Holiday Finds: How Pinterest Engineers Reimagined Gift Discovery

Pinterest Engineering

Megan Blake, Usha Amrutha Nookala, Jeremy Browning, Sarah Tao, AJ Oxendine, SiddarthMalreddy Overview &Context The holiday shopping season presents a unique challenge: helping millions of Pinners discover and save perfect gifts across a vast sea of possibilities. While Pinterest has always been a destination for gift inspiration, our data showed that users were facing two key friction points: discovery overwhelm and fragmented wishlists.

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Advanced Neural Networks for Generative AI

Edureka

With the advent of generative AI, the creative and innovative capabilities of machines have been greatly enhanced. It all comes down to sophisticated neural network architectures that try to imitate human intellect in order to make realistic films, images, and text. Transformers power conversational agents and GANs generate photorealistic art; these models are altering businesses.

More Trending

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Can AI be deployed in Critical Processes? Addressing the Key Challenges

DareData

Youve seen it before: a company starts deploying AI but struggles to move beyond the most high-level use cases. Yet, current AI technology has the potential to power near-fully automated business workflowsso whats missing? The challenge lies in how you manage the error. In critical business processes, AI errors can be extremely costly and deploying these systems becomes far more complex.

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DeepBrain AI: A Complete Explanation

Edureka

Imagine a future where connecting with technology is as natural as conversing with a friend. That is the idea behind DeepBrain AI, a groundbreaking platform that is altering how people engage with AI. DeepBrain AI enables organizations and individuals to effortlessly create, communicate, and develop, with lifelike virtual avatars and intelligent automation.

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A Guide to Integrating ChatGPT with Google Sheets

KDnuggets

This guide provides a detailed, step-by-step explanation of how to connect ChatGPT with Google Sheets, along with practical examples and advanced features to make the most of this integration.

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Vector Technologies for AI: Extending Your Existing Data Stack

Simon Späti

The database landscape has reached 394 ranked systems across multiple categoriesrelational, document, key-value, graph, search engine, time series, and the rapidly emerging vector databases. As AI applications multiply quickly, vector technologies have become a frontier that data engineers must explore. The essential questions to be answered are: When should you choose specialized vector solutions like Pinecone, Weaviate, or Qdrant over adding vector extensions to established databases like Post

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

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Foundation Model for Personalized Recommendation

Netflix Tech

By Ko-Jen Hsiao , Yesu Feng and Sudarshan Lamkhede Motivation Netflixs personalized recommender system is a complex system, boasting a variety of specialized machine learned models each catering to distinct needs including Continue Watching and Todays Top Picks for You. (Refer to our recent overview for more details). However, as we expanded our set of personalization algorithms to meet increasing business needs, maintenance of the recommender system became quite costly.

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Announcing Anthropic Claude 3.7 Sonnet is natively available in Databricks

databricks

Were excited to announce that Anthropic Claude 3.7 Sonnet is now natively available in Databricks across AWS, Azure, and GCP. For the first time, you.

AWS 139
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7 GitHub Projects to Master Machine Learning

KDnuggets

Learn model serving, CI/CD, ML orchestration, model deployment, local AI, and Docker to streamline ML workflows, automate pipelines, and deploy scalable, portable AI solutions effectively.

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Data Engineering Weekly #213

Data Engineering Weekly

Editor’s Note: Data Council 2025, Apr 22-24, Oakland, CA Data Council has always been one of my favorite events to connect with and learn from the data engineering community. Data Council 2025 is set for April 22-24 in Oakland, CA. As a special perk for Data Engineering Weekly subscribers, you can use the code dataeng20 for an exclusive 20% discount on tickets!

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Apache Airflow® Best Practices: DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!

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Unleashing GenAI — Ensuring Data Quality at Scale (Part 2)

Wayne Yaddow

Unleashing GenAIEnsuring Data Quality at Scale (Part2) Transitioning from individual repository source systems to consolidated AI LLM pipelines, the importance of automated checks, end-to-end observability, and compliance with enterprise businessrules. T Introduction There are several opportunities (and needs!) to improve operational effectiveness and analytical capacity when integrating data repository systems for AI Large Language Model (LLM) pipelines.

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Data contracts and Bitol project

Waitingforcode

Data contracts was a hot topic in the data space before LLMs and GenAI came out. They promised a better world with less communication issues between teams, leading to more reliable and trustworthy data. Unfortunately, the promise has been too hard to put into practice. Has been, or should I write "was"?

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Snowflake Ventures Invests in DataOps.live Bringing Advanced DevOps Capabilities to the AI Data Cloud

Snowflake

Todays organizations recognize the importance of data-driven decision-making, but the process of setting up a data pipeline thats easy to use, easy to track and easy to trust continues to be a complex challenge. Reducing time to success allows organizations to see immediate value from their data investments and scale up productivity. Our investment in DataOps.live , a SaaS platform for data engineering and operations, will help Snowflake users accelerate that timeline.

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TAO: Using test-time compute to train efficient LLMs without labeled data

databricks

Large language models are challenging to adapt to new enterprise tasks. Prompting is error-prone and achieves limited quality gains, while fine-tuning requires large amounts of.

Data 128
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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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The Future of Reliable Data + AI—Observing the Data, System, Code, and Model

Monte Carlo

AI can do a lot these days. At this very moment, an army of SaaS companies are hard at work infusing AI assistants and copilots into every horizontal B2B workflow currently known to humankind. ChatGPT can summarize the web to help sales prospects. Gemini can polish Google documents for research teams. GitHub copilot can even code alongside you like your own pocket-sized Steve Wozniak.

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An IBM Z Data Integration Success Story

Precisely

In today’s fast-paced digital world, maintaining high standards and addressing contemporary requirements is crucial for any company. One of our customers, a leading automotive manufacturer, relies on the IBM Z for its computing power and rock-solid reliability. However, they faced a growing challenge: integrating and accessing data across a complex environment.

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What is Retrieval-Augmented Generation (RAG)?

WeCloudData

Retrieval-augmented generation (RAG) is an AI cutting-edge approach that combines the power of traditional retrieval-based techniques with the capabilities of a generative large language model (LLM) to enhance the accuracy and relevance of AI-generated content. Instead of depending entirely on pre-trained knowledge, RAG incorporates external knowledge sources, such as documents or databases, to enhance the […] The post What is Retrieval-Augmented Generation (RAG)?

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How to Reach $500K on Upwork

KDnuggets

Check out the story of a Reddit user who has achieved success by following 7 simple rules.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Unleashing GenAI — Ensuring Data Quality at Scale (Part 1)

Wayne Yaddow

Unleashing GenAIEnsuring Data Quality at Scale (Part1) Transitioning from isolated repository systems to consolidated AI LLM pipelines Photo by Joshua Sortino on Unsplash Introduction This blog is based on insights from articles in Database Trends and Applications, Feb/Mar 2025 ( DBTA Journal ). Across these informative articles, one message rings loud and clear: Artificial intelligence (AI)and large language models (LLMs) in particularrequires relentless attention to dataquality.

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CycleGAN: A Generative Model for Image-to-Image Translation

Edureka

CycleGAN is a powerful Generative Adversarial Network (GAN) optimized for unpaired image-to-image translation. CycleGAN, unlike traditional GANs, does not require paired datasets, in which each image in one domain corresponds to an image in another. This makes it extremely useful for tasks that require collecting paired data, which can be difficult or impossible.

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Natural Language Processing(NLP) in Manufacturing

WeCloudData

Natural Language Processing (NLP) is transforming the manufacturing industry by enhancing decision-making, enabling intelligent automation, and improving quality control. As Industry 4.0 continues to evolve, NLP is becoming an essential tool for gaining insights from unstructured data, increasing productivity, and reducing human error. Lets learn more about the use cases of NLP in manufacturing and […] The post Natural Language Processing(NLP) in Manufacturing appeared first on WeCloudData

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Building an Automatic Speech Recognition System with PyTorch & Hugging Face

KDnuggets

Check out this step-by-step guide to building a speech-to-text system with PyTorch & Hugging Face.

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Apache Airflow® 101 Essential Tips for Beginners

Apache Airflow® is the open-source standard to manage workflows as code. It is a versatile tool used in companies across the world from agile startups to tech giants to flagship enterprises across all industries. Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.

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dbt on Databricks

Confessions of a Data Guy

Running dbt on Databricks has never been easier. The integration between dbtcore and Databricks could not be more simple to set up and run. Wondering how to approach running dbt models on Databricks with SparkSQL? Watch the tutorial below. The post dbt on Databricks appeared first on Confessions of a Data Guy.

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Webinar: Announcing Actionable, Automated, & Agile Data Quality Scorecards – 2024

DataKitchen

Announcing Actionable, Automated, & Agile Data Quality Scorecards Are you ready to unlock the power of influence to transform your organizations data qualityand become the hero your data deserves? Watch the previously recorded webinar unveiling our latest innovation: Data Quality Scorecards, powered by our AI-driven DataOps Data Quality TestGen software.

Data 52
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Guide to Masked Language Models (MLMs)

Edureka

Masked Language Models, also called MLMs, have truly emerged as a revolution in the Natural Language Processing (NLP) paradigm. They allow machines to achieve near-human performance in understanding and functioning in human language. They do this by masking certain words in a sentence and training the models to predict these missing words, thereby modeling the contextual relationships between words for a richer understanding of language.

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Land Your Dream Machine Learning Job in 2025

KDnuggets

In this article, I will go through 5 pointers on how to help you secure your dream job.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.