#MachineLearning for Streaming Data with Python — build practical online Machine Learning solutions: http://
amzn.to/40ztysN v/ @PacktDataML ——————
#DataScience #ML #AI #EdgeComputing #Edge #EdgeAI #TimeSeries #IoT #IIoT #DataScientist #AnomalyDetection
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Machine Learning for Streaming Data — practical online ML in Python
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Machine Learning for Time Series: Forecasting & Anomaly Detection
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Machine Learning for #TimeSeries with Python — Forecast trends, Predict the future, Detect anomalies with state-of-the-art ML methods: http://
amzn.to/3xf5ZdI by @benji1a ——————
#DataScience #AI #Forecasting #PredictiveAnalytics #AnomalyDetection #IoT #IIoT #DataScientist -
Building iPhone Apps with Codex in 2026
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I really love building iPhone apps in Codex. Codex can design the screens, write the Swift code with GPT-5.5, run the app in Simulator without opening Xcode, and even click around with computer use to test it!
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Strategic necessity of domestic AI hardware manufacturing
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Président @EmmanuelMacron si j'étais vous je donnerais immédiatement l'ordre de créer une grande usine de composants électroniques de dernière génération pour les besoins de l’IA sur le territoire français. C'est déjà trop tard mais il n'est jamais trop tard pour bien faire.
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Text-Conditional JEPA for Learning Semantically Rich Visual Representations
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Text-Conditional JEPA for Learning Semantically Rich Visual Representations Paper: https://
arxiv.org/abs/2605.03245 -
Apple Researchers Introduce TC-JEPA for Vision-Language Learning
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Looks like Apple is very interested in JEPA! What if your AI could “read” an image’s caption to solve visual puzzles? Apple researchers present TC-JEPA: a new self-supervised method that uses image captions to guide masked patch predictions. By conditioning on text, the model
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Causal Software Engineering: A Vision and Roadmap
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Causal Software Engineering: A Vision and Roadmap Paper: https://
arxiv.org/abs/2605.02454 -
Introducing Causal Software Engineering for Cause-and-Effect Modeling
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What if your software could tell you not just what went wrong, but what would have happened if you acted differently? Enter Causal Software Engineering (CSE). Instead of just spotting patterns in code or logs, CSE builds cause-and-effect models that answer interventional
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YUVA AI course expands AI education accessibility in India
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YUVA AI for ALL பாடநெறி, இந்தியா முழுவதும் AI கல்வியை மேலும் எளிதாகவும் அனைவருக்கும் அணுகக்கூடியதாகவும் மாற்றுகிறது. மொழி தடைகளை நீக்குவதன் மூலம், இந்தப் பாடநெறி மேலும் பல கற்றலாளர்கள் AI-ஐ புரிந்துகொள்ளவும், பயன்படுத்தவும், அன்றாட வாழ்க்கையில் செயல்படுத்தவும் உதவுகிறது. இன்றே
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Using HTML for LLM context building
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I never liked .md Been using html for most context building since last year. My thesis has been, if it trained on the entire internet, surely there must be more html than .md? And creating context that’s easier for me to digest was more important than using .md