Python first principles data von nayak ravindra (5 Ergebnisse)
Sprache: Englisch
Verlag: Independently Published, 2026
- Softcover
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Independently Published, 2026
- Softcover
Anbieter: PBShop.store US, Wood Dale, IL, USAPBShop.store US
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Independently Published, 2026
- Softcover
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Independently Published, 2026
- Softcover
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Python First Principles for Data Scientists and Developers Volume 8 : The AI and Automation Workshop
Sprache: Englisch
Verlag: Amazon Digital Services LLC - Kdp Mai 2026, 2026
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Volume 1 helped you understand Python thinking.Volume 2 helped you build practical programs.Volume 3 helped you organize information with data structures.Volume 4 helped you work with real data using NumPy and pandas.Volume 5 helped you visualize data and think statistically.Volume 6 helped y…ou enter machine learning responsibly.Volume 7 helped you build professional Python tools.Volume 8 brings Python into the modern AI and automation world.AI can feel mysterious. Prompts, models, tokens, embeddings, APIs, RAG, agents, and automation workflows can sound overwhelming to beginners. But behind the noise, the first principles are simple: input, context, reasoning support, output, evaluation, and human judgment.Python First Principles for Data Scientists and Developers - Volume 8: The AI and Automation Workshop explains AI-assisted building step by step.This volume teaches readers how to use Python with large language models, design better prompts, call APIs, structure AI outputs, search meaning with embeddings, build beginner-friendly RAG systems, understand agentic workflows, evaluate AI responses, protect privacy, and use AI responsibly in data science and software development.Inside this volume, readers will learn: How LLMs fit into the Python developer's workflowHow prompts work as instructions, context, and constraintsHow to use APIs safely and practicallyHow structured outputs make AI results more reliableHow embeddings represent meaningHow semantic search finds ideas, not just keywordsHow RAG connects documents with AI responsesHow agents use tools, steps, and feedback loopsHow to evaluate AI outputs instead of trusting them blindlyHow to use AI for data science assistanceHow to use AI for developer productivityHow to think about safety, privacy, bias, and responsible automationHow to build practical AI-assisted capstone projectsThis is not a hype-driven AI book.It is a practical workshop for building with AI calmly and responsibly.By the end of Volume 8, readers will understand how Python, AI models, automation, and human judgment work together.AI is not a replacement for thinking.AI is a tool that becomes powerful when guided by clear thinking.
