Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications Overview 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 In Detail With the increasing prominence in machine learning and data science applications, probabilistic graphical models are a new tool that machine learning users can use to discover and analyze structures ...