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Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale

KDnuggets

By KDnuggets on June 11, 2025 in Partners Sponsored Content Recommender systems rely on data, but access to truly representative data has long been a challenge for researchers. In recent years, several new datasets have been made public that aim to better reflect real-world usage patterns, spanning music, e-commerce, advertising, and beyond.

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Top 10 Data Engineering & AI Trends for 2025

Monte Carlo

2025 data engineering trends incoming. Synthetic data works by leveraging models to create artificial datasets that reflect what someone might find organically (in some alternate reality where more data actually exists), and then using that new data to train their own models. Table of Contents 1. Process > Tooling (Barr) 3.

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AI Agents in Analytics Workflows: Too Early or Already Behind?

KDnuggets

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 AI Agents in Analytics Workflows: Too Early or Already Behind? Here, SQL stepped in.

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PyTorch vs TensorFlow 2025-A Head-to-Head Comparison

ProjectPro

PyTorch vs Tensorflow 2025– Comparing the Similarities and Differences PyTorch and Tensorflow both are open-source frameworks with Tensorflow having a two-year head start to PyTorch. However, if you are a researcher then it would be a good step to get started with PyTorch. PREVIOUS NEXT <

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Data Engineering Roadmap, Learning Path,& Career Track 2025

ProjectPro

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. Interact with the data scientists team and assist them in providing suitable datasets for analysis. That needs to be done because raw data is painful to read and work with.

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

But as we move into 2025, organizations are facing new challenges that are testing their data strategies, artificial intelligence (AI) readiness, and overall trust in data. Read on for the highlights from this panel – including actionable tips to ensure success in your 2025 data, analytics, and AI initiatives.

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Integrating DuckDB & Python: An Analytics Guide

KDnuggets

By Josep Ferrer , KDnuggets AI Content Specialist on June 10, 2025 in Python Image by Author DuckDB is a fast, in-process analytical database designed for modern data analysis. This works similarly to if-else statements in programming languages, allowing you to apply conditional logic in your queries.

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