Overview of this book
<p><span id="description" class="sugar_field">Bayesian methods have grown recently because of their success in solving hard data analytics problems. They are rapidly becoming a must-have in every data scientists toolkit. The course uses a hands-on method to teach you how to use Bayesian methods to solve data analytics problems in the real world. You will understand the principles of estimation, inference, and hypothesis testing using the Bayesian framework. You will also learn to use them to solve problems such as A/B testing, understanding consumer habits, risk evaluation, adjusting machine learning predictions, reliability analysis, detecting the influence of one variable over an outcome, and many others.</span></p>
<p><span id="description" class="sugar_field">By taking this course, you will be able to apply and use Bayesian methods as part of your data analytics toolbox, thus helping you use Python to solve a majority of common statistical problems in data science.<br /> </span></p>
<p><span id="description" class="sugar_field">The code bundle for this course is available at - <a style="font-weight: normal;" href="https://github.com/PacktPublishing/-Hands-On-Bayesian-Methods-with-Python" target="_new">https://github.com/PacktPublishing/-Hands-On-Bayesian-Methods-with-Python</a></span></p>
<h1><span class="sugar_field">Style and Approach</span></h1>
<p><span class="sugar_field"><span id="trade_selling_points_c" class="sugar_field"><span id="trade_selling_points_c" class="sugar_field">The course follows a hands-on approach; explanations of core concepts are intuitive and always related to applications. Interesting real-world examples are presented and solved using computational methods, especially the PyMC3 library. Mathematics are used only when necessary.</span></span></span></p>
