Download Free Introduc A Las Matematicas Neg Book in PDF and EPUB Free Download. You can read online Introduc A Las Matematicas Neg and write the review.

"MATEMATICAS BASICAS. Una Introducción al Cálculo" tiene una fácil manera para aprender a aprender Matemáticas con cuatro capítulos principales; el primero está referido a la teoría de conjuntos, el sistema numérico y la recta real, junto con el sistema cartesiano del plano y espacio. El segundo capítulo muestra aplicaciones de la teoría de conjuntos, las permutaciones, las combinaciones, las relaciones y las funciones. El tercer capítulo ilustra traslaciones y modelos funcionales con los tipos de funciones: real, polinómica, constante, lineal, cuadrática, exponencial, logarítmica, trigonométricas y función inversa. El cuarto capítulo desarrolla las ecuaciones y desigualdades, junto con sistemas de ecuaciones y desigualdades lineales o no lineales. El quinto capítulo concluye con ejercicios de recapitulación resueltos. Esta obra está dirigida a estudiantes universitarios en programas académicos presenciales o de educación a distancia en ciencias económicas, administrativas, sociales y humanísticas.
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
After the success of the first edition, Introduction to Functional Programming using Haskell has been thoroughly updated and revised to provide a complete grounding in the principles and techniques of programming with functions. The second edition uses the popular language Haskell to express functional programs. There are new chapters on program optimisation, abstract datatypes in a functional setting, and programming in a monadic style. There are complete new case studies, and many new exercises. As in the first edition, there is an emphasis on the fundamental techniques for reasoning about functional programs, and for deriving them systematically from their specifications. The book is self-contained, assuming no prior knowledge of programming and is suitable as an introductory undergraduate text for first- or second-year students.
Contents include an elementary but thorough overview of mathematical logic of 1st order; formal number theory; surveys of the work by Church, Turing, and others, including Gödel's completeness theorem, Gentzen's theorem, more.