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maureen dawson retweeted
Carney's so-called "AI" policy is pixie dust. Tinker Bell would be proud. #Canada #machinelearningtools #sentencecompletionmachine #bullshite
Yes - there is danger all around.
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The AI/ML software stack is a layered toolkit that covers the full AI/ML workflow ๐Ÿ˜Ž๐Ÿ‘‡ Find high-res pdf ebooks with all my #technology related infographics at study-notes.org/technology-iโ€ฆ #machinelearning #machinelearningtools #ai #deeplearning #softwarestack
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AI & ML in Trade Surveillance ๐Ÿง ๐Ÿ” Modern surveillance systems go beyond rule-based alerts to understand trading behavior and intent. Swipe to see how intelligence replaces noise! What else is changing: Real-time detection of market abuse and manipulation Fewer false positives through adaptive ML models Cross-market and time-sequence analysis at scale Explore VLinkโ€™s to build surveillance that anticipates risk โšก tinyurl.com/2ukemp5m #artificialintellegence #ai #artificial #machinelearning #datascience #artificialintelligencenow #machinelearningtools #data #science #learning #machine #machinelearningengineer #VLinkInc
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Microchip Technology introduced a new set of fullโ€‘stack solutions designed to simplify and accelerate the development of edge artificial intelligence (AI) systems. newelectronics.co.uk/contentโ€ฆ #EdgeAI #MachineLearningTools #EmbeddedSystems

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Most RAG setups look perfectly fine at first glanceโ€ฆ until you dig in and realize half the retrieved chunks arenโ€™t even relevant ๐Ÿ˜… Thatโ€™s the silent killer of RAG performance, you donโ€™t just have bad outputs, you have bad inputs feeding the model from the start. Thatโ€™s exactly where RAGAS becomes a game-changer. It doesnโ€™t just tell you โ€œyour RAG isnโ€™t working.โ€ It scores every part of your pipeline โ€” retrieval relevance, hallucination likelihood, answer coverage, reasoning alignment, and more. All the invisible failure modes that you cannot catch by just reading responses manually. In the bootcamp, we use RAGAS as a diagnostic tool: we test โ†’ measure โ†’ fix each step โ†’ test again. No more guessing. No more hoping the retrieval was good. Just measurable improvements that make your agents 10ร— more accurate and reliable. If you want to build RAG systems based on engineering, not guesswork, Register now for our upcoming Agentic AI Bootcamp happening in January & February -> hubs.la/Q03XkD7T0 ๐Ÿš€ #RAG #RAGAS #LLMEngineering #AIAgents #AgenticAI #RetrievalAugmentedGeneration #AIEngineering #LLMRetrieval #AIOptimization #MachineLearningTools #AIForDevelopers
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AI/ML-based Bank Statement Analyser- AI-Driven Financial Insights for confident decisions !!! . . #OPL #OPLInnovate #opltechnology #Fintechsolutions #BusinessFinance #AIDriven #ML #BankStatementAnalyzer #APIintegration #MachineLearningTools
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23 Sep 2025
๐Ÿ’ก What if a single trade error could trigger millions in losses? From T 1 settlement pressure to real-time compliance, post-trade ops are under the microscope. Level up your post-trade lifecycle with us: tinyurl.com/2bpyrvdp ๐Ÿ’ผ No more bottlenecks. Just intelligent automation, STP gains, and zero-error reconciliation. #artificialintellegence #ai #artificial #machinelearning #datascience #artificialintelligencenow #machinelearningtools #data #science #learning #machine #VLinkInc
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๐Ÿ” The AI Tools Ecosystem for 2025 โ€” simplified in one map. #AITools #AgenticAI #AIecosystem #FutureOfAI #AIinnovation #MachineLearningTools #AIagents #NextGenAI #AIWorkflows
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7 Aug 2025
Glimpses of Certification Course on Python for Machine Learning for 5th Semester C Division Students. #klesociety #rlsbca #rlsibca #rlsbcabelagavi #autonomouscollege #klebcabelagavi #certificationsAtRlsBca #certificationcourse #python #machinelearning #machinelearningtools
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6 Aug 2025
Glimpses of Certification Course on Python for Machine Learning for 5th Semester A Division Students. #klesociety #rlsbca #rlsibca #rlsbcabelagavi #autonomouscollege #klebcabelagavi #certificationsAtRlsBca #certificationcourse #python #machinelearning #machinelearningtools
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Machine Learning Tools To Elevate Your Skills ow.ly/BahF50VRgBq #MachineLearning #ML #MachineLearningTools
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๐Ÿง  ๐‚ ๐ข๐ง ๐€๐ˆ: ๐๐จ๐ญ ๐‰๐ฎ๐ฌ๐ญ ๐๐ฒ๐ญ๐ก๐จ๐ง ๐Ÿš€ Python may be the poster child for AIโ€”but C is the ๐ฆ๐ฎ๐ฌ๐œ๐ฅ๐ž ๐ฎ๐ง๐๐ž๐ซ ๐ญ๐ก๐ž ๐ก๐จ๐จ๐. This infographic unpacks where ๐‚ ๐ก๐จ๐ฅ๐๐ฌ ๐ข๐ญ๐ฌ ๐ ๐ซ๐จ๐ฎ๐ง๐ (๐š๐ง๐ ๐ž๐ฏ๐ž๐ง ๐จ๐ฎ๐ญ๐ฉ๐š๐œ๐ž๐ฌ) ๐๐ฒ๐ญ๐ก๐จ๐ง in AI development, and when to leverage each like a pro: โšก ๐’๐ฉ๐ž๐ž๐ C delivers blazing ๐ž๐ฑ๐ž๐œ๐ฎ๐ญ๐ข๐จ๐ง ๐ฉ๐ž๐ซ๐Ÿ๐จ๐ซ๐ฆ๐š๐ง๐œ๐ž, ideal for real-time inference, custom ML engines, or GPU-intensive tasks. Python? Smooth and flexibleโ€”but ๐ฌ๐ฅ๐จ๐ฐ๐ž๐ซ ๐ฎ๐ง๐๐ž๐ซ ๐ญ๐ก๐ž ๐ก๐จ๐จ๐, often relying on C -based libraries. ๐Ÿ“ฆ ๐ƒ๐ž๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐ž๐ง๐ญ C compiles into ๐ฌ๐ž๐ฅ๐Ÿ-๐œ๐จ๐ง๐ญ๐š๐ข๐ง๐ž๐ ๐›๐ข๐ง๐š๐ซ๐ข๐ž๐ฌ, making it ideal for ๐ž๐๐ ๐ž ๐๐ž๐ฏ๐ข๐œ๐ž๐ฌ, ๐ฅ๐จ๐ฐ-๐ฅ๐š๐ญ๐ž๐ง๐œ๐ฒ ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆs, and platforms where Python environments are bulky. Python excels in ๐ฉ๐ซ๐จ๐ญ๐จ๐ญ๐ฒ๐ฉ๐ข๐ง๐  ๐š๐ง๐ ๐€๐๐ˆ-๐Ÿ๐ข๐ซ๐ฌ๐ญ ๐๐ž๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐ž๐ง๐ญ๐ฌ, but may require Dockerization or virtual environments. ๐Ÿ–ฅ๏ธ ๐‡๐š๐ซ๐๐ฐ๐š๐ซ๐ž ๐‚๐จ๐ง๐ญ๐ซ๐จ๐ฅ C = full access to ๐ฆ๐ž๐ฆ๐จ๐ซ๐ฒ ๐ฆ๐š๐ง๐š๐ ๐ž๐ฆ๐ž๐ง๐ญ, ๐ฉ๐š๐ซ๐š๐ฅ๐ฅ๐ž๐ฅ ๐ฉ๐ซ๐จ๐œ๐ž๐ฌ๐ฌ๐ข๐ง๐ , ๐ž๐ฆ๐›๐ž๐๐๐ž๐ ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆ๐ฌ, ๐š๐ง๐ ๐†๐๐”/๐…๐๐†๐€-๐ฅ๐ž๐ฏ๐ž๐ฅ ๐ญ๐ฎ๐ง๐ข๐ง๐ . Python abstracts hardware complexity, favoring easeโ€”but ๐ฅ๐ž๐ฌ๐ฌ ๐ฌ๐ฎ๐ซ๐ ๐ข๐œ๐š๐ฅ ๐œ๐จ๐ง๐ญ๐ซ๐จ๐ฅ. ๐Ÿง‘โ€๐Ÿ’ป ๐ƒ๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ฆ๐ž๐ง๐ญ ๐’๐ฉ๐ž๐ž๐ Python is ๐Ÿ๐š๐ฌ๐ญ๐ž๐ซ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ž, debug, and iterate. C requires more effort but shines when ๐ฉ๐ซ๐ž๐œ๐ข๐ฌ๐ข๐จ๐ง ๐š๐ง๐ ๐ž๐Ÿ๐Ÿ๐ข๐œ๐ข๐ž๐ง๐œ๐ฒ outweigh developer convenience. ๐ŸŒ ๐„๐œ๐จ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆ Python boasts massive libraries: TensorFlow, PyTorch, Hugging Face, and a thriving ML community. C has fewer high-level AI librariesโ€”but underpins many Python packages with ๐œ๐จ๐ซ๐ž ๐œ๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ž ๐ฅ๐ข๐›๐ซ๐š๐ซ๐ข๐ž๐ฌ ๐ฅ๐ข๐ค๐ž ๐„๐ข๐ ๐ž๐ง, ๐Ž๐๐๐— ๐‘๐ฎ๐ง๐ญ๐ข๐ฆ๐ž, ๐š๐ง๐ ๐‹๐ข๐›๐“๐จ๐ซ๐œ๐ก. ๐ŸŽฏ ๐”๐ฌ๐ž ๐‚๐š๐ฌ๐ž๐ฌ C : ๐‡๐ข๐ ๐ก-๐ฉ๐ž๐ซ๐Ÿ๐จ๐ซ๐ฆ๐š๐ง๐œ๐ž ๐ข๐ง๐Ÿ๐ž๐ซ๐ž๐ง๐œ๐ž ๐ž๐ง๐ ๐ข๐ง๐ž๐ฌ, ๐ž๐ฆ๐›๐ž๐๐๐ž๐ ๐€๐ˆ, ๐ซ๐จ๐›๐จ๐ญ๐ข๐œ๐ฌ, ๐€๐‘/๐•๐‘, ๐š๐ฎ๐ญ๐จ๐ง๐จ๐ฆ๐จ๐ฎ๐ฌ ๐ฏ๐ž๐ก๐ข๐œ๐ฅ๐ž๐ฌ Python: ๐‘๐ž๐ฌ๐ž๐š๐ซ๐œ๐ก, ๐ž๐ฑ๐ฉ๐ž๐ซ๐ข๐ฆ๐ž๐ง๐ญ๐š๐ญ๐ข๐จ๐ง, ๐ฆ๐จ๐๐ž๐ฅ ๐ญ๐ซ๐š๐ข๐ง๐ข๐ง๐ , ๐๐‹๐, ๐‚๐•, ๐ฉ๐ซ๐จ๐ญ๐จ๐ญ๐ฒ๐ฉ๐ข๐ง๐  ๐ŸŽ“ ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐  ๐‚๐ฎ๐ซ๐ฏ๐ž Python wins in ๐ž๐š๐ฌ๐ž ๐จ๐Ÿ ๐ฅ๐ž๐š๐ซ๐ง๐ข๐ง๐  ๐š๐ง๐ ๐ซ๐ž๐š๐๐š๐›๐ข๐ฅ๐ข๐ญ๐ฒ. C demands ๐ฆ๐จ๐ซ๐ž ๐ฅ๐จ๐ฐ-๐ฅ๐ž๐ฏ๐ž๐ฅ ๐ฎ๐ง๐๐ž๐ซ๐ฌ๐ญ๐š๐ง๐๐ข๐ง๐  ๐š๐ง๐ ๐๐ž๐›๐ฎ๐ ๐ ๐ข๐ง๐  ๐ฌ๐ค๐ข๐ฅ๐ฅ๐ฌ. ๐Ÿ”— ๐ˆ๐ง๐ญ๐ž๐ ๐ซ๐š๐ญ๐ข๐จ๐ง Best of both worlds: use ๐๐ฒ๐ญ๐ก๐จ๐ง ๐Ÿ๐จ๐ซ ๐ฆ๐จ๐๐ž๐ฅ ๐๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ฆ๐ž๐ง๐ญ, export to ๐‚ ๐Ÿ๐จ๐ซ ๐๐ž๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐ž๐ง๐ญ. Tools like ONNX, Pybind11, and TorchScript bridge the gap. ๐Ÿ’ฌ ๐๐จ๐ญ๐ญ๐จ๐ฆ ๐‹๐ข๐ง๐ž: Donโ€™t just ask โ€œPython vs. C โ€โ€”ask ๐ฐ๐ก๐ž๐ง ๐š๐ง๐ ๐ฐ๐ก๐ž๐ซ๐ž. Because in the real world of AI, ๐๐ฒ๐ญ๐ก๐จ๐ง ๐ฉ๐ซ๐จ๐ญ๐จ๐ญ๐ฒ๐ฉ๐ž๐ฌ. ๐‚ ๐ฉ๐จ๐ฐ๐ž๐ซ๐ฌ ๐ฉ๐ซ๐จ๐๐ฎ๐œ๐ญ๐ข๐จ๐ง. ๐ŸŒ pcdoctorsnet.com ๐Ÿ“ž 1 (346) 355-6002 #CppInAI #PythonVsCpp #AIEngineering #EdgeAI #MachineLearningTools #AIFrameworks #HighPerformanceAI #EdgeAI #DeepLearningDeployment #CppForML #PythonAndCpp #BrainAndBuild #AIDevelopment #MachineLearning #PythonAndCpp #SmartDeployment #texas #usa #UnitedStates #pcdoctorsnet #canada #india
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