Libros de Otros lenguajes, página 24 de 187

A substantially revised third edition of a comprehensive textbook that covers a broad range of topics not often included in introductory texts. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing. Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.

La Web y las apps para dispositivos móviles se ha convertido en parte imprescindible de nuestras vidas; desde las consultas y búsquedas de información, a disfrutar de las redes sociales, y realizar compras o numerosas gestiones o tramites. CSS ha permitido que todos los elementos que componen el codigo se muestren ante el usuario con una atractiva apariencia, la estructura y los efectos deseados, permitiendo al visitante una eficiente usabilidad y una autentica experiencia de usuario.Esta obra nos muestra cuales son las herramientas necesarias y como usarlas para generar hojas de estilos en cascada imprescindibles para todo diseñador, maquetador o desarrollador front en su trabajo diario. Presenta las tecnicas actuales que nos brinda CSS3 sin olvidar las ya existentes, y las que nos deparan versiones futuras. Se abordara el cross browsing para que nuestros estilos, animaciones y efectos se apliquen correctamente en cualquier navegador, y el diseño adaptativo y responsive para que el mismo codigo muestre distintos resultados en funcion del dispositivo (movil, tableta, ordenador, etc.) en el que se visualice. Ademas, cuenta con ejemplos practicos y reales, extrapolables a cualquier proyecto.