Machine Learning: Hands-On for Developers and Technical Professionals

Machine Learning: Hands-On for Developers and Technical Professionals

(1 reviews, 833 downloads)
, 2014-11-03, 408 pages, pdf, epub
Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals….
Computer Vision Metrics: Survey, Taxonomy, and Analysis

Computer Vision Metrics: Survey, Taxonomy, and Analysis

(4 reviews, 700 downloads)
, 2014-05-22, 508 pages, pdf, epub
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about…
Building Probabilistic Graphical Models with Python

Building Probabilistic Graphical Models with Python

(2 reviews, 890 downloads)
, 2014-05-25, 172 pages, pdf, epub
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…
State of the Art Applications of Social Network Analysis

State of the Art Applications of Social Network Analysis

(1 reviews, 737 downloads)
, 2014-05-27, 372 pages, pdf, epub
Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory,…
High Performance Python: Practical Performant Programming for Humans

High Performance Python: Practical Performant Programming for Humans

(1 reviews, 1986 downloads)
, 2014-09-20, 370 pages, pdf, epub
Your Python code may run correctly, but you need it to run faster. By exploring the fundamental theory behind design choices, this practical guide helps you gain a deeper understanding of Python’s implementation. You’ll learn how to locate performance bottlenecks…