url stringlengths 13 1.72k | title stringlengths 1 655 | category stringclasses 37 values | tags listlengths 0 4 | score int64 1 9 | source stringclasses 8 values |
|---|---|---|---|---|---|
https://www.linkedin.com/feed/update/urn:li:activity:7419699566603603968?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7419699566603603968%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Ralf D. Müller — New Semantic Anchor: Pyramid Principle 🔺
Working with LLMs? Long explanations c | Context Engineering | [
"semantic anchor",
"LLMs",
"explanations"
] | 7 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7416584818605330432?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7416584818605330432%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Rene Pajta — 𝗠𝘆 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝘁𝗶𝗺𝗲 𝘀𝗶𝗻𝗸 𝗮𝘀 𝗖𝗵𝗶𝗲𝗳 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝘄𝗮𝘀 𝗻𝗼𝘁 𝗰𝗼𝗱𝗶𝗻𝗴. 𝗜𝘁 𝘄𝗮𝘀 𝗰𝗼𝗻𝘁𝗲𝘅𝘁. 🧠
When | Context Engineering | [
"context",
"architecture",
"challenges"
] | 7 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7389621490696097792?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7389621490696097792%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Shirin Khosravi Jam — Context engineering is the #1 skill for building production AI agents.
4 documen | Context Engineering | [
"production AI",
"skills",
"context engineering"
] | 9 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7321207890503962624?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7321207890503962624%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Steve Nouri — Why GPT 4.1 isn’t just an upgrade, it’s a whole new mindset for prompting.🔥
Jus | Context Engineering | [
"GPT-4.1",
"prompting",
"mindset"
] | 8 | linkedin |
https://blog.logrocket.com/ux-design/designing-ai-with-prompt-sets/?ref=dailydev | Stop writing PRDs for AI — start using prompt sets instead - LogRocket Blog | Context Engineering | [
"prompt-sets",
"AI",
"product-requirements"
] | 7 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7414279717790339072?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7414279717790339072%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Sumanth P — Finally, an open-source data backend for Context Engineering!
Acontext is an op | Context Engineering | [
"open-source",
"data backend"
] | 8 | linkedin |
https://www.analyticsvidhya.com/blog/2023/05/what-is-prompt-engineering-guide/ | The Art of Crafting Powerful Prompts: A Guide to Prompt Engineering | Context Engineering | [
"prompt engineering",
"guide",
"crafting"
] | 9 | raindrop |
https://www.tensorlake.ai/blog-posts/context-driven-enterprise-platform | The Next Enterprise Platform Isn't Data-Driven, It's Context-Driven | Context Engineering | [
"context-driven",
"enterprise",
"platform"
] | 7 | edge |
https://www.kdnuggets.com/the-only-prompting-framework-for-every-use?ref=dailydev | The Only Prompting Framework for Every Use | Context Engineering | [
"prompting",
"framework"
] | 7 | raindrop |
https://app.daily.dev/posts/the-ultimate-prompt-to-make-ai-write-like-a-human-ekmhvn0la | The Ultimate Prompt to Make AI Write Like a Human | Context Engineering | [
"Prompt Engineering",
"AI Writing"
] | 7 | dailydev |
https://bartwullems.blogspot.com/2025/09/the-prompt-as-documentation-should-ai.html?ref=dailydev | The prompt as documentation: Should AI-generated code include its origin story? | Context Engineering | [
"documentation",
"ai-code"
] | 6 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7188868780905644033?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7188868780905644033%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Tibi David — Still struggling to get good responses from ChatGPT in 2024? Let me show you my | Context Engineering | [
"ChatGPT",
"responses",
"improvement"
] | 8 | linkedin |
https://claw.toggle.pro/?ref=producthunt | Toggle × OpenClaw — The Context Layer | Context Engineering | [
"context",
"layer"
] | 7 | edge |
https://app.daily.dev/posts/ultimate-prompting-guide-for-veo-3-1-w74nff0ct | Ultimate prompting guide for Veo 3.1 | Context Engineering | [
"prompting",
"guide"
] | 7 | dailydev |
https://app.daily.dev/posts/vertex-ai-context-caching-idss94ga4 | Vertex AI context caching | Context Engineering | [
"context caching",
"Vertex AI"
] | 8 | dailydev |
https://neo4j.com/blog/genai/what-is-context-engineering/ | What Is Context Engineering in AI? A Practical Guide - Graph Database & Analytics | Context Engineering | [
"context engineering",
"guide"
] | 9 | edge |
https://newsletter.systemdesign.one/p/what-is-context-engineering?ref=dailydev | What is Context Engineering | Context Engineering | [
"context engineering"
] | 8 | edge |
https://app.daily.dev/posts/what-is-context-engineering--kbsgndy9c | What is Context Engineering? | Context Engineering | [
"context engineering"
] | 7 | dailydev |
https://www.decube.io/post/context-engineering-ai?ref=dailydev | What is Context Engineering? | Decube | Context Engineering | [
"context",
"engineering",
"AI"
] | 8 | edge |
https://www.coderabbit.ai/ja/blog/show-me-the-prompt-what-to-know-about-prompt-requests?ref=dailydev | What to know about prompt requests | Context Engineering | [
"prompt requests"
] | 7 | edge |
https://app.daily.dev/posts/why-ai-fails-without-context-and-why-multimodel-data-platforms-are-becoming-the-new-enterprise-sta-szdk4g9mu | Why AI Fails Without Context — And Why Multimodel Data Platforms Are Becoming the New Enterprise Standard • Arango | daily.dev | Context Engineering | [
"context",
"multimodel"
] | 8 | edge |
https://app.daily.dev/posts/your-prompts-are-bad-here-s-how-to-fix-them--trcl3dosr | Your Prompts Are Bad. Here’s How to Fix Them. | daily.dev | Context Engineering | [
"Prompts",
"Improvement"
] | 7 | edge |
https://app.daily.dev/posts/your-rag-system-has-a-hidden-ux-problem-oytm7rbu2 | Your RAG System Has a Hidden UX Problem | daily.dev | Context Engineering | [
"rag",
"ux"
] | 7 | edge |
https://github.com/davidkimai/Context-Engineering | davidkimai/Context-Engineering: "Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspired by Karpathy and 3Blue1Brown for moving beyond prompt engineering to the wider discipline of context design, orchestration, and optimization. | Context Engineering | [
"context",
"engineering"
] | 9 | edge |
https://github.com/gsd-build/get-shit-done | gsd-build/get-shit-done: A light-weight and powerful meta-prompting, context engineering and spec-driven development system for Claude Code by TÂCHES. | Context Engineering | [
"meta-prompting",
"context-engineering",
"development"
] | 8 | edge |
https://github.com/kayba-ai/agentic-context-engine | kayba-ai/agentic-context-engine: 🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai | Context Engineering | [
"agent",
"learning",
"experience"
] | 8 | edge |
https://app.daily.dev/posts/avkfnqgvq | volcengine/MineContext: MineContext is your proactive context-aware AI partner（Context-Engineering+ChatGPT Pulse） | daily.dev | Context Engineering | [
"context-aware",
"ChatGPT"
] | 8 | edge |
https://app.daily.dev/posts/why-agents-can-t-live-without-fresh-data-cntxcesok | why agents can't live without fresh data | daily.dev | Context Engineering | [
"agents",
"data"
] | 7 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7374728984732942336?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7374728984732942336%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | 👋🏼 Jochem van Laren — Most people still chase clever prompts…
…and end up with AI answers that feel ge | Context Engineering | [
"prompts",
"AI answers",
"misconceptions"
] | 6 | linkedin |
https://app.daily.dev/posts/gomask-ai-instant-compliant-test-data-for-engineering-teams-nlb6bn8xm | (2) GoMask.ai: Instant compliant test data for engineering teams | daily.dev | Data Science & ML | [
"test data",
"engineering",
"compliance"
] | 6 | edge |
https://www.kdnuggets.com/2023/04/10-websites-get-amazing-data-data-science-projects.html?utm_source=rss&utm_medium=rss&utm_campaign=10-websites-to-get-amazing-data-for-data-science-projects | 10 Websites to Get Amazing Data for Data Science Projects - KDnuggets | Data Science & ML | [
"data",
"resources",
"projects"
] | 8 | raindrop |
https://blog.dailydoseofds.com/p/4-parallel-processing-techniques?ref=dailydev | 4 Parallel Processing Techniques in Python - by Avi Chawla | Data Science & ML | [
"parallel processing",
"Python",
"techniques"
] | 6 | edge |
https://www.kdnuggets.com/2023/04/5-essential-ai-tools-data-science.html?utm_source=rss&utm_medium=rss&utm_campaign=5-essential-ai-tools-for-data-science | 5 Essential AI Tools for Data Science - KDnuggets | Data Science & ML | [
"data science",
"ai tools",
"essential tools"
] | 8 | raindrop |
https://www.nannyml.com/blog/91-of-ml-perfomance-degrade-in-time | 91% of ML Models Degrade in Time - NannyML | Data Science & ML | [
"ML models",
"degrade",
"performance"
] | 8 | raindrop |
https://www.kdnuggets.com/2023/04/guide-top-natural-language-processing-libraries.html?utm_source=rss&utm_medium=rss&utm_campaign=a-guide-to-top-natural-language-processing-libraries | A Guide to Top Natural Language Processing Libraries - KDnuggets | Data Science & ML | [
"NLP",
"libraries",
"guide"
] | 8 | raindrop |
https://www.marktechpost.com/2023/05/04/a-new-ai-research-introduces-a-method-to-answer-questions-by-meta-reasoning-over-multiple-chains-of-thought/ | A New AI Research Introduces A Method To Answer Questions By Meta-Reasoning over Multiple Chains of Thought | Data Science & ML | [
"meta-reasoning",
"AI research"
] | 9 | raindrop |
https://app.daily.dev/posts/ai-ml-workflows-with-singlestore-thmlnivml | AI ML workflows with SingleStore | Data Science & ML | [
"AI ML workflows",
"SingleStore"
] | 7 | dailydev |
https://www.infoworld.com/article/4128925/ai-augmented-data-quality-engineering.html?ref=dailydev | AI-augmented data quality engineering | InfoWorld | Data Science & ML | [
"data",
"quality",
"engineering"
] | 7 | edge |
https://www.abundant.ai/ | Abundant — Frontier RL environments and datasets | Data Science & ML | [
"reinforcement-learning",
"datasets"
] | 8 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7379425345348923392?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7379425345348923392%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Alex Razvant — Are GPUs the optimal hardware for Transformer Inference?
GPUs currently handle | Data Science & ML | [
"GPUs",
"Transformer",
"inference"
] | 6 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7386661472795467776?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7386661472795467776%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Alex Wang — How deep does AI already run in your industry?
This super practical report from | Data Science & ML | [
"industry",
"AI report"
] | 6 | linkedin |
https://svghub.vercel.app/?ref=dailydev | All Machine Learning algorithms explained in 17 min | Data Science & ML | [
"machine learning",
"algorithms"
] | 9 | raindrop |
https://www.linkedin.com/feed/update/urn:li:activity:7425478552403300352?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7425478552403300352%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | AlphaSignal — We solved "Code Generation." Now we’re facing the "Verification Gap."
Teams hea | Data Science & ML | [
"Code Generation",
"Verification Gap",
"teams"
] | 6 | linkedin |
https://analytics-with-c1.vercel.app/?threadId=89951894-65c8-4312-8298-9f76abfaa538 | Analytics + C1 | Data Science & ML | [
"analytics",
"c1"
] | 6 | edge |
https://reposecgo.com/scan# | Analyze Repository Security | RepoSecGo | Data Science & ML | [
"repository",
"security",
"analysis"
] | 7 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7435395982583988224?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7435395982583988224%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Anindya Dey, PhD — My recent article published in Towards Data Science on the Sharpness-Aware Minim | Data Science & ML | [
"Sharpness-Aware Minimization",
"article",
"Towards Data Science"
] | 6 | linkedin |
https://spark.apache.org/ | Apache Spark™ - Unified Engine for large-scale data analytics | Data Science & ML | [
"apache-spark",
"data-analytics",
"big-data"
] | 9 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7419375472054235136?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7419375472054235136%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Arjun Sarath — SQL is the wrong tool for traceability.
When we started building Synter to hand | Data Science & ML | [
"SQL",
"Traceability",
"Synter"
] | 6 | linkedin |
https://www.autoanalyst.ai/ | Auto-Analyst | Data Science & ML | [
"Auto-Analyst",
"AI"
] | 8 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7026499417461469185?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7026499417461469185%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Avi Chawla — I reviewed 1,000+ Python libraries and discovered these hidden gems I never knew | Data Science & ML | [
"Python",
"Libraries",
"Review"
] | 7 | linkedin |
https://azimutt.app/?ref=producthunt | Azimutt · Database explorer and analyzer | Data Science & ML | [
"database",
"exploration",
"analysis"
] | 7 | raindrop |
https://blog.dailydoseofds.com/p/build-portable-ml-models-with-onnx?ref=dailydev | Build Portable ML Models with ONNX - by Avi Chawla | Data Science & ML | [
"onnx",
"ml models",
"portable"
] | 8 | edge |
https://app.daily.dev/posts/can-llm-embeddings-improve-time-series-forecasting-a-practical-feature-engineering-approach-3yqwulpwj | Can LLM Embeddings Improve Time Series Forecasting? A Practical Feature Engineering Approach | Data Science & ML | [
"LLM",
"Time Series Forecasting"
] | 9 | dailydev |
https://www.kdnuggets.com/2023/03/chatgpt-data-science-cheat-sheet.html?utm_source=rss&utm_medium=rss&utm_campaign=chatgpt-for-data-science-cheat-sheet | ChatGPT for Data Science Cheat Sheet - KDnuggets | Data Science & ML | [
"chatgpt",
"data science",
"cheat sheet"
] | 8 | raindrop |
https://app.daily.dev/posts/codalogy-visualize-any-codebase-instantly-ubfpqt0dr | Codalogy: Visualize Any Codebase Instantly | Data Science & ML | [
"visualization",
"codebase"
] | 6 | dailydev |
https://app.daily.dev/posts/compare-ai-video-models-replicate-blog-xlh0lxj7t | Compare AI video models – Replicate blog | Data Science & ML | [
"AI video models",
"comparison"
] | 6 | dailydev |
https://blog.dailydoseofds.com/p/comparing-the-top-open-source-ocr?ref=dailydev | Comparing the Top Open-source OCR Solutions - by Avi Chawla | Data Science & ML | [
"OCR",
"solutions"
] | 6 | edge |
https://blog.sentry.io/core-kpis-llm-performance-how-to-track-metrics/?utm_source=dailydev&utm_medium=paid-community&utm_campaign=llm-fy26q4-corekpisebook&utm_content=static-ad-dailydev-site-learnmore | Core KPI Metrics of LLM Performance and How to Track Them | Sentry | Data Science & ML | [
"llm-performance",
"metrics",
"tracking"
] | 8 | edge |
https://app.daily.dev/posts/correlation-vs-cosine-similarity-wgaju1vlw | Correlation vs. cosine similarity | Data Science & ML | [
"Correlation",
"Cosine Similarity"
] | 7 | dailydev |
https://www.migraven.com/en/produkte/preisrechner/ | Cost-benefit calculator › Holistic data management made in Germany | Data Science & ML | [
"calculator",
"data management",
"cost-benefit"
] | 5 | edge_bookmarks |
https://cratedb.com/blog/distributed-database-real-time-analytics?ref=dailydev | CrateDB Blog | Distributed Database Explained for Real-Time Analytics | Data Science & ML | [
"CrateDB",
"analytics",
"database"
] | 7 | edge |
https://manus.im/app/BnOlNw1TUH1weh26Y963lo | Creating Artifacts for Nexus Brain DB and Security Report - Manus | Data Science & ML | [
"nexus",
"brain",
"db"
] | 6 | edge |
https://www.producthunt.com/posts/data-explorer-2 | Data Explorer - Explore GitHub live data in natural language | Product Hunt | Data Science & ML | [
"github",
"data"
] | 8 | raindrop |
https://www.confluent.io/blog/data-streaming-platforms-ai/?ref=dailydev | Data Streaming Platform: The Key to AI Success | Data Science & ML | [
"data streaming",
"AI"
] | 7 | edge |
https://www.dailydoseofds.com/mlops-crash-course-part-6/#data-leakage | Data and Pipeline Engineering: Sampling, Data Leakage, and Feature Stores | Data Science & ML | [
"data",
"pipeline",
"engineering"
] | 7 | edge |
https://www.r-bloggers.com/2026/02/december-2025-top-40-new-cran-packages/?ref=dailydev | December 2025 Top 40 New CRAN Packages | R-bloggers | Data Science & ML | [
"cran",
"packages",
"new"
] | 5 | edge |
https://aisharenet.com/deepseek-ocr/ | DeepSeek-OCR - DeepSeek开源的光学字符识别模型 | AI分享圈 | Data Science & ML | [
"OCR",
"AI"
] | 6 | edge_bookmarks |
https://blog.dailydoseofds.com/p/detect-production-grade-code-quality?ref=dailydev | Detect Production-grade Code Quality Issues in Real-time! | Data Science & ML | [
"code quality",
"production",
"real-time"
] | 7 | edge |
https://keras.io/guides/distribution/ | Distributed training with Keras 3 | Data Science & ML | [
"keras",
"distributed training"
] | 7 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7405152833739636736?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7405152833739636736%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Dr. Alexander Jarasch — Extracting insights from your “information dead ends,” also known as PDFs?
Bring | Data Science & ML | [
"insights",
"PDFs"
] | 5 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7062675292976214016?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7062675292976214016%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Dr. Moritz Lehmann — With slow commercial #CFD software, compute time for my #PhD studies would have | Data Science & ML | [
"CFD",
"Software",
"PhD"
] | 5 | linkedin |
https://www.codecentric.de/en/knowledge-hub/blog/duckdb-vs-polars-performance-and-memory-with-massive-parquet-data?ref=dailydev | DuckDB vs. Polars: Performance & Memory on Parquet Data | Data Science & ML | [
"duckdb",
"polars",
"performance"
] | 7 | edge |
https://dyna.org/?ref=dailydev | Dyna — Logic Programming for Machine Learning | Data Science & ML | [
"logic programming",
"machine learning"
] | 8 | edge |
https://blog.bytebytego.com/p/ep193-database-types-you-should-know?ref=dailydev | EP193: Database Types You Should Know in 2025 | Data Science & ML | [
"database",
"types",
"2025"
] | 6 | edge |
https://app.daily.dev/posts/earthgpt-ai-powered-remote-sensing-ldlavs58l | EarthGPT — AI-Powered Remote Sensing | Data Science & ML | [
"remote sensing",
"AI"
] | 7 | dailydev |
https://aisharenet.com/egocentric-10k/ | Egocentric-10K - Build AI开源的第一人称视角机器人数据集 | AI分享圈 | Data Science & ML | [
"dataset",
"robotics",
"AI"
] | 7 | edge_bookmarks |
https://projector.tensorflow.org/ | Embedding projector - visualization of high-dimensional data | Data Science & ML | [
"embedding",
"visualization",
"high-dimensional"
] | 8 | edge |
https://dev.migraven.com/ | Ganzheitliches Datenmanagement made in Germany | Data Science & ML | [
"data management",
"germany",
"holistic"
] | 5 | edge_bookmarks |
https://keras.io/keras_hub/api/models/gemma/gemma_backbone/#getlayoutmap-method | GemmaBackbone model | Data Science & ML | [
"keras",
"gemma",
"model"
] | 6 | edge |
https://www.kdnuggets.com/2023/02/getting-started-python-generators.html?utm_source=rss&utm_medium=rss&utm_campaign=getting-started-with-python-generators | Getting Started with Python Generators - KDnuggets | Data Science & ML | [
"Python",
"generators",
"introduction"
] | 7 | raindrop |
https://github.com/HKUDS/AI-Trader | HKUDS/AI-Trader: "AI-Trader: Can AI Beat the Market?" Live Trading Bench: https://ai4trade.ai Tech Report Link: https://arxiv.org/abs/2512.10971 | Data Science & ML | [
"ai-trader",
"market",
"trading"
] | 8 | edge |
https://lab.cloud/ | Hello from Transformer Lab | Transformer Lab | Data Science & ML | [
"Transformer Lab",
"AI"
] | 8 | edge |
https://www.analyticsvidhya.com/blog/2023/03/how-to-classify-web-pages-using-machine-learning/ | How to Classify Web Pages Using Machine Learning? | Data Science & ML | [
"web-classification",
"ml",
"tutorial"
] | 8 | raindrop |
https://www.singlestore.com/blog/ml-functions-bring-models-to-data/ | Introducing ML Functions in SingleStore: Bring Models to the Data | Data Science & ML | [
"ml",
"functions",
"singlestore"
] | 7 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7034179780656644099?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7034179780656644099%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Jeremy Dalton — Did you know you have free access to a 3D model of New York City that you can in | Data Science & ML | [
"3D Model",
"New York City",
"Access"
] | 5 | linkedin |
https://www.ssp.sh/brain/kaggle/#using-duckdb-to-read-datasets-with-extension | Kaggle | Data Science & ML | [
"kaggle",
"datasets"
] | 8 | edge |
https://www.kaggle.com/ | Kaggle: Your Machine Learning and Data Science Community | Data Science & ML | [
"kaggle",
"community",
"data science"
] | 8 | raindrop |
https://machinelearningmastery.com/llm-embeddings-vs-tf-idf-vs-bag-of-words-which-works-better-in-scikit-learn/?ref=dailydev | LLM Embeddings vs TF-IDF vs Bag-of-Words: Which Works Better in Scikit-learn? - MachineLearningMastery.com | Data Science & ML | [
"LLM",
"embeddings",
"Scikit-learn"
] | 8 | edge |
https://docs.databricks.com/aws/en/ldp/concepts | Lakeflow Spark Declarative Pipelines concepts | Databricks on AWS | Data Science & ML | [
"databricks",
"spark",
"pipelines"
] | 8 | edge |
https://keras.io/api/distribution/layout_map/ | LayoutMap API | Data Science & ML | [
"keras",
"layout map",
"API"
] | 6 | edge |
https://docs.lancedb.com/training | Loading Data for Model Training - LanceDB | Data Science & ML | [
"data",
"model",
"training"
] | 8 | edge |
https://thepalindrome.org/p/making-ai-cheaper-smaller-and-faster-9ed?ref=dailydev | Making Neural Networks Cheaper, Smaller, and Faster | Data Science & ML | [
"neural networks",
"optimization"
] | 8 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7432772045131804672?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7432772045131804672%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Malte Ostendorff — Introducing CommonLID - a new language identification benchmark for web data, co | Data Science & ML | [
"language identification",
"benchmark"
] | 5 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7433411413215334400?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7433411413215334400%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Marktechpost AI Media Inc — Google DeepMind Introduces Unified Latents (UL): A Machine Learning Framework th | Data Science & ML | [
"Machine Learning",
"Unified Latents"
] | 8 | linkedin |
https://www.linkedin.com/feed/update/urn:li:activity:7433176648088219648?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7433176648088219648%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Mayank A. — how do you programmatically test if your AI-generated media is actually high qua | Data Science & ML | [
"AI-generated media",
"quality testing"
] | 5 | linkedin |
https://www.marktechpost.com/2022/11/12/meet-this-artificial-intelligence-ai-image-dataset-called-diffusiondb-that-consists-of-2-million-stable-diffusion-images-and-their-text-prompts-and-hyperparameters/ | Meet This Artificial Intelligence (AI) Image Dataset Called 'DIFFUSIONDB,' That Consists of 2 Million Stable Diffusion Images, And Their Text Prompts And Hyperparameters | Data Science & ML | [
"dataset",
"stable-diffusion"
] | 8 | raindrop |
https://www.linkedin.com/feed/update/urn:li:activity:7339231225535983617?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7339231225535983617%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Merve Noyan — Dolphin: new OCR model by ByteDance with MIT license 🐬 https://lnkd.in/gz8a_t_w
| Data Science & ML | [
"OCR",
"ByteDance"
] | 7 | linkedin |
https://metaflow.org/ | Metaflow - a framework for real-life ML, AI, and data science | Data Science & ML | [
"Metaflow",
"framework",
"ML"
] | 8 | edge |
https://www.linkedin.com/feed/update/urn:li:activity:7301884512039239681?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7301884512039239681%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29 | Michael Wade — A very interesting benchmark for how well different AI models understand the wor | Data Science & ML | [
"benchmark",
"AI models",
"understanding"
] | 7 | linkedin |
https://app.daily.dev/posts/modular-manifolds-aarfmt096 | Modular Manifolds | Data Science & ML | [] | 5 | dailydev |
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