#DeepLearning with PyTorch… 1) Cheat sheet [PDF]: https://
dropbox.com/scl/fi/e4xngyk
rfoubiw3xnd6fz/PyTorch-Cheatsheet.pdf?rlkey=vgx38ckps7aie120imgozgq4g&st=hgs06d4t&dl=0
… 2) Learn fundamentals with hands-on coding [PDF]: https://
dropbox.com/scl/fi/lfo7r6f
nd8wjm3gp0jteh/Learn-PyTorch-Deep-Learning-with-Hands-On-Code.pdf?rlkey=mg9cxg41yerouzp0rklm8hqa2&st=c7k7rgay&dl=0
… 3) #GenerativeAI with Python and PyTorch: https://
amzn.to/4fYjiBn book v/ @PacktDataML
MACHINE LEARNING
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PyTorch Deep Learning Resources: Cheat Sheet, Hands-On Guide, Generative AI
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Apache Spark Real-Time Mode Enables Millisecond Event Processing
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For years, Apache Spark™ Structured Streaming has powered mission-critical pipelines. Now, with real-time mode, it extends to workloads that process events in milliseconds — like fraud detection, live personalization, and real-time ML feature serving.
— Databricks (@databricks) 30 août 2025
Explore real-time mode in… pic.twitter.com/vQrltz5MU7For years, Apache Spark™ Structured Streaming has powered mission-critical pipelines. Now, with real-time mode, it extends to workloads that process events in milliseconds — like fraud detection, live personalization, and real-time ML feature serving. Explore real-time mode in
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Prompt for step-by-step reasoning via Chain of Thought
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2. Chain of Thought → Smarter Step-by-Step Answers Don’t just ask for an answer. Ask it to think out loud. This avoids shallow, “one-shot” answers. Prompt: Think step by step. Show your reasoning before giving the final answer.
If you’re unsure, list possible paths and then -
Designing Machine Learning Systems Book Summaries Resources
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8. Designing Machine Learning Systems This repo contains the summaries and resources for Designing Machine Learning Systems book – Github Repo:
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Design, develop, deploy production-grade ML applications
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5. Made with ML Learn how to design, develop, deploy and iterate on production-grade ML applications. – Github Repo:
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AIoT paradigm enables intelligent autonomous action across connected devices
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By merging sensing, analytics, and autonomy across interconnected devices, the AIoT paradigm shifts from mere data collection to intelligent action, opening new directions in how systems perceive, interpret, and respond to their environments. Microblog by @antgrasso
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Fine-tuning adoption challenges lack compelling success stories
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I think a bigger problem is the almost complete lack of fine tuning success stories – it's still really hard to find convincing stories of teams that used fine tuning for anything more interesting than "we got a cheap model to classify things slightly better"
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AI self-optimizing prompts shifts focus to curating evaluation criteria
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Once AI begins to self optimize prompts, the focus will shift from writing prompts to curating evaluation criteria.
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AI Boosts Ophthalmologist Diagnostic Accuracy to 92% in RCT
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Un essai randomisé en soins oculaires, comparant des ophtalmologistes avec IA à des ophtalmologistes sans IA, a démontré une précision de diagnostic bien supérieure (92 % contre 74 %), ainsi que de nombreux autres résultats améliorés. Aujourd'hui ,je le répète, ne pas utiliser
