SKU/Artículo: AMZ-B0GDYWPFZY
BAYESIAN INFERENCE WITH PYTHON FOR BEGINNERS: Understanding the Fundamentals of Bayesian Analysis with Python
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Kindle
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0.76 kg
0.76 kg
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Amazon
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USA
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- Bayesian Inference with Python for Beginners: Understanding the Fundamentals of Bayesian Analysis with Python Feeling overwhelmed by the complexity of statistical models and struggling to understand Bayesian Inference? If you're finding it difficult to dive into the world of Bayesian statistics with Python, you're not alone. Bayesian Inference with Python for Beginners offers a straightforward, step-by-step approach to learning one of the most powerful techniques in modern data science. Gone are the days of confusing jargon and overwhelming mathematical formulas, this book makes Bayesian Inference easy to understand and apply. Written for beginners, data enthusiasts, and those new to Bayesian statistics, "Bayesian Inference with Python for Beginners" is your ultimate guide to mastering the essentials of Bayesian analysis through hands-on Python coding. This isn’t just a textbook; it's your toolkit for unlocking the full potential of probabilistic modeling. Inside, you’ll find over practical examples and exercises to guide you through the concepts and get you coding confidently. Whether you're learning the basics or exploring into more advanced concepts, each chapter will give you the tools you need to apply Bayesian techniques to real-world problems. Here's why this book is a must-have: ✔️ Beginner-Friendly: No prior experience with Bayesian statistics or Python required. Every chapter is written in clear, simple language and includes practical coding exercises to reinforce key concepts. ✔️ Hands-On Python Code: Learn Bayesian Inference by doing. Each chapter includes code snippets and exercises that allow you to experiment and apply the concepts immediately. ✔️ Code Examples for Real-World Problems: From basic probability to model building, this book includes Python code examples designed to solve real-world problems like regression, classification, and data analysis using Bayesian methods. These are the valuable skills you will gain: Understanding Probability Theory: Learn how to apply basic probability concepts in the context of Bayesian statistics. Bayesian Modeling with Python: Build your first Bayesian models using PyMC3 and other Python libraries. MCMC Sampling & Variational Inference: Master MCMC sampling and learn about modern techniques like Variational Inference to efficiently estimate complex models. Practical Data Analysis: Work with real data, applying Bayesian methods to make informed predictions and decisions. Evaluating Model Performance: Learn how to assess the performance of your Bayesian models with diagnostic tools like trace plots and posterior predictive checks. These are the key concepts you will explore: 🔹 Introduction to Bayesian Probability: Grasp the core idea of updating beliefs with new data and understand how Bayes’ Theorem works. 🔹 Working with Priors and Likelihoods: Learn how to choose appropriate priors and compute likelihoods to update your models. 🔹 MCMC Sampling: Dive into Markov Chain Monte Carlo methods to sample from posterior distributions, a crucial part of advanced Bayesian modeling. 🔹 Model Evaluation and Diagnostics: Master tools for checking convergence, assessing model fit, and making sure your results are reliable. 🔹 Hierarchical Models and Advanced Techniques: Understand hierarchical modeling and other advanced Bayesian concepts that will elevate your skills. Don’t let uncertainty hold you back from mastering Bayesian Inference! Invest in your future by gaining a deep understanding of probabilistic modeling and statistical analysis with Python. Ready to unlock the power of Bayesian Inference? Click on Buy Now and Start Your Journey Today!
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