"Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neura…
"Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neura…
DEEP LEARNING A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and b…
Introduction to R -- Data Vizualization & Dashboards: Best practices -- Geospatial Data: Understanding changing baseball player behavior -- Machine Learning Basics: Modeling football draft patterns, pick number & clusters among athletes -- Logistic Regression: Explaining basketb…
"R is an open-source, freely available programming language used throughout this book. R is a powerful and longstanding programming language developed more than 20 years ago. It is a derivative of the "S" programming language for statistics originating in the mid-nineties develo…
"R is an open-source, freely available programming language used throughout this book. R is a powerful and longstanding programming language developed more than 20 years ago. It is a derivative of the "S" programming language for statistics originating in the mid-nineties develo…
This book provides a practical introduction to mathematics for economics using R software. Using R as a basis, this book guides the reader through foundational topics in linear algebra, calculus, and optimization. The book is organized in order of increasing difficulty, beginnin…
"This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book bala…
"The subject of this textbook is to act as an introduction to data science / data analysis applied to finance, using R and its most recent and freely available extension libraries. The targeted academic level is undergrad students with a major in data science and/or finance and …