{"product_id":"bayesian-inference-python-for-beginners-a-step-by-step-guide-to-probabilistic-programming-no-advanced-math-required-9798253507858","title":"Bayesian Inference Python for Beginners: A Step-by-Step Guide to Probabilistic Programming - No Advanced Math Required","description":"\u003cp\u003e • Author(s): Eluan Dan\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Data Science - Data Analytics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eMost statistics books make you feel like you need a PhD just to read the introduction. This one does the opposite.\u003c\/p\u003e\u003cp\u003eIf you have ever stared at a p-value and wondered what it actually means, watched colleagues build probabilistic models and felt left out, or suspected that traditional statistics was leaving something important on the table - this book was written for you.\u003c\/p\u003e\u003cp\u003eBayesian inference powers spam filters, clinical trials, A\/B testing systems, and fraud detection models running at scale every single day. With Python libraries like PyMC 5 and ArviZ 1.0, it has never been more accessible to practitioners who can code but were never formally trained in statistics.\u003c\/p\u003e\u003cp\u003eThis book teaches you Bayesian inference the way it should be taught - through clear explanations, runnable Python code, and real-world problems you can relate to immediately.\u003c\/p\u003e\u003cp\u003eNo PhD required. No advanced calculus. No impenetrable equation blocks.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eHere is what you will master inside: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eHow Bayesian thinking differs from traditional statistics and why it produces more honest, actionable results\u003c\/li\u003e\n\u003cli\u003eBayes' theorem explained in plain English, visualized in Python, and applied to real problems including medical testing and spam classification\u003c\/li\u003e\n\u003cli\u003eA complete Bayesian Python environment setup using PyMC 5, ArviZ 1.0, and JupyterLab - with a full troubleshooting guide\u003c\/li\u003e\n\u003cli\u003eThe probability distributions that appear in almost every real Bayesian model, with code and clear guidance on when to use each one\u003c\/li\u003e\n\u003cli\u003eHow to build models in PyMC from scratch, defining priors, likelihoods, and posteriors in readable Python you will understand line by line\u003c\/li\u003e\n\u003cli\u003eMCMC sampling demystified through a from-scratch implementation you build yourself\u003c\/li\u003e\n\u003cli\u003eModel diagnostics using trace plots, R-hat, effective sample size, and divergence checks - and how to fix what is broken\u003c\/li\u003e\n\u003cli\u003eBayesian linear regression, A\/B testing, hierarchical models, and classification - all with full code and real-world scenarios\u003c\/li\u003e\n\u003cli\u003eThree complete capstone projects covering customer churn prediction, time series forecasting, and clinical trial analysis\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eEvery chapter closes with a hands-on mini-project that gives you something concrete to build, run, and keep.\u003c\/p\u003e\u003cp\u003eWhether you are a Python developer curious about probabilistic programming, a data analyst tired of significance thresholds, a bootcamp graduate who never got a proper statistics education, or a professional in healthcare, finance, or marketing who works with uncertain data every day - this book gives you the foundation to reason clearly and model honestly.\u003c\/p\u003e\u003cp\u003eIf you are ready to build models that tell the truth about what they know and what they do not, and make decisions from data with genuine statistical integrity - your next step starts here.\u003c\/p\u003e\u003cp\u003e\u003ci\u003e\u003cb\u003eGrab your copy and start thinking like a Bayesian today.\u003c\/b\u003e\u003c\/i\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47775754485911,"sku":"9798253507858","price":3156.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798253507858.webp?v=1777992256","url":"https:\/\/atlanticbooks.com\/products\/bayesian-inference-python-for-beginners-a-step-by-step-guide-to-probabilistic-programming-no-advanced-math-required-9798253507858","provider":"Atlantic Books","version":"1.0","type":"link"}