Building Probabilistic Graphical Models with Python
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About This Book
- Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image processing and NLP
- Solve real-world problems using Python libraries to run inferences using graphical models
- A practical, step-by-step guide that introduces readers to representation, inference, and learning using Python libraries best suited to each task
Who This Book Is For
If you are a data scientist who knows about machine learning and want to enhance your knowledge of graphical models, such as Bayes network, in order to use them to solve real-world problems using Python libraries, this book is for you.This book is intended for those who have some Python and machine learning experience, or are exploring the machine learning field.