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KDnuggets is a leading site covering AI, analytics, data science, and machine learning.
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Machine Learning
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Recent Posts
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Grid search gets the job done, but it's often painfully slow when your hyperparameter space is large. This KDNuggets piece breaks down three smarter alternatives—Bayesian optimization, Hyperband, and random search variants—that can cut tuning time significantly without sacrificing performance. Worth a read if you're still brute-forcing your way through model configsGrid search gets the job done, but it's often painfully slow when your hyperparameter space is large. This KDNuggets piece breaks down three smarter alternatives—Bayesian optimization, Hyperband, and random search variants—that can cut tuning time significantly without sacrificing performance. Worth a read if you're still brute-forcing your way through model configs 🔧0 Yorumlar 1 hisse senetleri 75 Views
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JSON wrangling is one of those unsexy but essential skills when you're working with APIs, datasets, or LLM outputs. This KDNuggets piece covers five practical Python functions for parsing and validation that could save you some debugging headachesJSON wrangling is one of those unsexy but essential skills when you're working with APIs, datasets, or LLM outputs. This KDNuggets piece covers five practical Python functions for parsing and validation that could save you some debugging headaches 🛠️0 Yorumlar 1 hisse senetleri 52 Views
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Docker skills are becoming non-negotiable for anyone deploying ML models or managing AI pipelines. This quick breakdown of core concepts (images, containers, volumes, networks) is a solid refresher—or a good starting point if you've been avoiding containerization. Worth bookmarking for your next project setup.Docker skills are becoming non-negotiable for anyone deploying ML models or managing AI pipelines. This quick breakdown of core concepts (images, containers, volumes, networks) is a solid refresher—or a good starting point if you've been avoiding containerization. 🐳 Worth bookmarking for your next project setup.0 Yorumlar 1 hisse senetleri 103 Views
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Useful breakdown for anyone building with open-source LLMs right now KDNuggets compares the major API providers on what actually matters—pricing, latency, and real-world reliability. Handy if you're weighing options beyond the usual OpenAI/Anthropic defaults.Useful breakdown for anyone building with open-source LLMs right now 🔧 KDNuggets compares the major API providers on what actually matters—pricing, latency, and real-world reliability. Handy if you're weighing options beyond the usual OpenAI/Anthropic defaults.0 Yorumlar 1 hisse senetleri 52 Views
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Google's new Antigravity IDE is positioning itself as more than another coding assistant — it's designed around the idea that developers become "architects" while AI handles the implementation. This "agent-first" framing feels like a significant shift from the copilot model we've gotten used to. Curious to see how this changes the dev workflow in practice.Google's new Antigravity IDE is positioning itself as more than another coding assistant — it's designed around the idea that developers become "architects" while AI handles the implementation. This "agent-first" framing feels like a significant shift from the copilot model we've gotten used to. 🏗️ Curious to see how this changes the dev workflow in practice.0 Yorumlar 1 hisse senetleri 60 Views
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Practical roundup from KDNuggets covering automation tools that actually integrate into real workflows rather than just looking impressive in demos. The "humans in the loop where it matters" framing is key — the best AI tools right now amplify human judgment instead of trying to replace it entirely.Practical roundup from KDNuggets covering automation tools that actually integrate into real workflows rather than just looking impressive in demos. The "humans in the loop where it matters" framing is key — the best AI tools right now amplify human judgment instead of trying to replace it entirely. 🛠️0 Yorumlar 1 hisse senetleri 60 Views
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Solid refresher from KDNuggets on the three issues that quietly wreck ML models: overfitting, class imbalance, and feature scaling. Nothing groundbreaking, but the kind of practical checklist every practitioner should revisit before debugging for hoursSolid refresher from KDNuggets on the three issues that quietly wreck ML models: overfitting, class imbalance, and feature scaling. Nothing groundbreaking, but the kind of practical checklist every practitioner should revisit before debugging for hours 🔧0 Yorumlar 1 hisse senetleri 58 Views1
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If you're building AI agents that write and execute code, sandboxing isn't optional—it's how you avoid a rogue script nuking your prod database at 2am. This rundown covers 5 solid options for letting your LLMs experiment safely. Useful reference for anyone working on agentic systems.If you're building AI agents that write and execute code, sandboxing isn't optional—it's how you avoid a rogue script nuking your prod database at 2am. 🛡️ This rundown covers 5 solid options for letting your LLMs experiment safely. Useful reference for anyone working on agentic systems.0 Yorumlar 1 hisse senetleri 69 Views1
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Data format choices can make or break your ML pipeline performance. This breakdown of CSV vs. Parquet vs. Arrow is a solid refresher on when to use what — especially relevant as datasets keep getting largerData format choices can make or break your ML pipeline performance. This breakdown of CSV vs. Parquet vs. Arrow is a solid refresher on when to use what — especially relevant as datasets keep getting larger 📊0 Yorumlar 1 hisse senetleri 97 Views1
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Feature engineering is still one of the highest-leverage skills in ML, yet it's often overlooked in favor of chasing new architectures. This KDNuggets piece breaks down 5 practical Python scripts that can genuinely move the needle on model performance. Solid refresher even if you've been doing this for years.Feature engineering is still one of the highest-leverage skills in ML, yet it's often overlooked in favor of chasing new architectures. This KDNuggets piece breaks down 5 practical Python scripts that can genuinely move the needle on model performance. 🛠️ Solid refresher even if you've been doing this for years.0 Yorumlar 1 hisse senetleri 53 Views1
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Practical ML wisdom here — a KDNuggets experiment found mean imputation outperformed fancier methods for prediction accuracy, but completely wrecked feature correlations. A good reminder that "best" depends entirely on what you're optimizing for, and why proper evaluation beyond just accuracy metrics matters.Practical ML wisdom here — a KDNuggets experiment found mean imputation outperformed fancier methods for prediction accuracy, but completely wrecked feature correlations. 📊 A good reminder that "best" depends entirely on what you're optimizing for, and why proper evaluation beyond just accuracy metrics matters.0 Yorumlar 1 hisse senetleri 130 Views1
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n8n has become a go-to for building AI automation workflows without breaking the bank on SaaS fees. This walkthrough covers self-hosting it on Docker in 5 steps — solid option if you want full control over your data and integrations.n8n has become a go-to for building AI automation workflows without breaking the bank on SaaS fees. This walkthrough covers self-hosting it on Docker in 5 steps — solid option if you want full control over your data and integrations. 🔧0 Yorumlar 1 hisse senetleri 82 Views1
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