Generative AI on Google Cloud with LangChain โ Design scalable Generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud: http://
amzn.to/4frbkPA v/ @PacktDataML ๐๐ฎ๐ ๐๐ฎ๐ช๐ฝ๐พ๐ป๐ฎ๐ผ:
Turn challenges into opportunities by learning advanced techniques for
MACHINE LEARNING
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Design Scalable Generative AI with LangChain and Vertex AI
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New book: RAG-Driven Generative AI (2nd ed.)
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New Release (2nd edition) from @PacktDataML available at http://
amzn.to/4tULP1b RAG-Driven Generative AI โ Build MAS-RAG with DualRAG, GraphRAG, multimodal video pipelines, and Oracle Database 23ai ๐๐ฒ๐ ๐๐ฒ๐ฎ๐๐๐ฟ๐ฒ๐:
Master DualRAG by combining vector search with SQL -
Machine Learning for Streaming Data โ practical online ML in Python
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#MachineLearning for Streaming Data with Python โ build practical online Machine Learning solutions: http://
amzn.to/40ztysN v/ @PacktDataML โโโโโโ
#DataScience #ML #AI #EdgeComputing #Edge #EdgeAI #TimeSeries #IoT #IIoT #DataScientist #AnomalyDetection -
Machine Learning for Time Series: Forecasting & Anomaly Detection
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Machine Learning for #TimeSeries with Python โ Forecast trends, Predict the future, Detect anomalies with state-of-the-art ML methods: http://
amzn.to/3xf5ZdI by @benji1a โโโโโโ
#DataScience #AI #Forecasting #PredictiveAnalytics #AnomalyDetection #IoT #IIoT #DataScientist -
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 โreadโ an imageโs 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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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 thatโs easier for me to digest was more important than using .md
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AutoGL Framework for Graph Machine Learning Datasets
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AutoGL: Framework For Graph Dataset! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/AutoGL-Datasets