This post is not about them I have been around long enough to see history repeating itself
RESEARCH
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Google Releases Gemma 4 Open Source AI Model Apache 2.0
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Google vient de lâcher Gemma 4 en open source. Et c'est un game changer.
— VISION IA (@vision_ia) 3 avril 2026
Licence Apache 2.0. Téléchargeable maintenant.
Construit à partir de la même recherche que Gemini 3, leur modèle propriétaire le plus puissant. Sauf que celui-là, vous pouvez le faire tourner chez vous.… https://t.co/TApkY3sg7jGoogle just released Gemma 4 in open source. And it's a game changer. Apache 2.0 license. Downloadable now. Built from the same research as Gemini 3, their most powerful proprietary model. Except this one, you can run it at home. No cloud. No subscription. No paying per token.
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Machine Learning Tracks Methane Emissions From Orbit
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Machine Learning Tracks Methane Emissions From Orbit! #BigData #Analytics #AI #MachineLearning #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/ML-Methane -
Dead Spiders Transformed into Robotic Grippers by Engineers
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Dead Spiders Reanimated as Necrobotic Grippers by Rice University Engineers
— Ronald van Loon (@Ronald_vanLoon) 3 avril 2026
by @IntEngineering#Innovation #TechForGood #EmergingTech #Technology pic.twitter.com/pKca0ZPo05Dead Spiders Reanimated as Necrobotic Grippers by Rice University Engineers
by @IntEngineering #Innovation #TechForGood #EmergingTech #Technology -
Google Releases Gemma 4 with Apache 2.0 Open Source License
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Google just re-entered the game 🔥🔥 They want to take the crown 👑 back from Chinese open source AI. And… Gemma 4 is FINALLY Apache 2.0 aka real-open-source-licensed. From what I've seen it's going to be a pretty significant model. But give it a try yourself today: brew install llama.cpp –HEAD if you have at least 24GB of RAM or VRAM, run the (very good) 26B MOE: llama-server -hf ggml-org/gemma-4-26B-A4B-it-GGUF:Q4_K_M if you have 16GB of RAM or VRAM, run the dense E4B: llama-server -hf ggml-org/gemma-4-E4B-it-GGUF:Q8_0
→ View original post on X — @huggingface, 2026-04-03 05:41 UTC
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Python Machine Learning By Example Third Edition Book Release
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Python Machine Learning By Example: http://
amzn.to/3MczBwk v/ @PacktDataML +
GitHub: https://
github.com/PacktPublishin
g/Python-Machine-Learning-By-Example-Third-Edition
… 518-pages! What you will learn: Machine learning best practices throughout data preparation and model development Build and improve image classifiers using -
Stanford’s Free AI Course: Transformers and Large Language Models
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If you’re serious about AI, this is worth your attention. Stanford has just released its course CME 295: Transformers & Large Language Models in full on YouTube. What stands out to me is the level of clarity and structure. This isn’t another surface-level overview. It’s the actual curriculum used to teach how modern AI systems work. This will help you move from using AI to understanding it. 📚 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: • How Transformers actually work (tokenization, attention, embeddings) • Decoding strategies & MoEs • LLM finetuning (LoRA, RLHF, supervised) • Evaluation techniques (LLM-as-a-judge) • Optimization tricks (RoPE, quantization, approximations) • Reasoning & scaling • Agentic workflows (RAG, tool calling) 🎥 Watch these now: – Lecture 1: zurl.co/F0QR5 – Lecture 2: zurl.co/hG5lp – Lecture 3: zurl.co/PnKrW – Lecture 4: zurl.co/XCZoE – Lecture 5: zurl.co/GWlYI – Lecture 6: zurl.co/zGqqQ – Lecture 7: zurl.co/T06NM – Lecture 8: zurl.co/Un42q – Lecture 9: zurl.co/rR3YL For 2026, consider setting aside 2–3 hours each week to go through these lectures. If you’re working in AI whether on infrastructure, agents, or applications, this is a foundational resource worth your time. It’s a simple way to build depth where it matters most. #AI #LLMs #Transformers #Stanford #GenAI
→ View original post on X — @pascal_bornet, 2026-04-03 05:00 UTC
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50 Essential Algorithms for Every Programmer to Learn
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50 Algorithms Every Programmer Should Know: http://
amzn.to/3Mi1hAk v/ @PacktDataML #DataScientist #DataScience #Mathematics #MachineLearning #ML #ComputerScience #ComputationalScience -
Python for Data Science: Hands-On Introduction Book
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Python for Data Science — A Hands-On Introduction: http://
amzn.to/44LcjEA
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#DataScience #AI #ML #MachineLearning #DataScientist -
Bayesian Data Analysis and Probabilistic Modeling in Python
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Bayesian Data Analysis [download 677-page PDF Statistics eBook] at http://
sites.stat.columbia.edu/gelman/book/
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Do it in Pythonusing this Practical Guide to Probabilistic Modeling: http://
amzn.to/3w3tq9g —————
#DataScience #DataScientist #MachineLearning #ML #Inference #StatisticalLearning