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Machine Learning

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Deep Learning (6)

e-books in Machine Learning category

Book cover: The Hundred-Page Machine Learning BookThe Hundred-Page Machine Learning Book
by ,
This is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
(745 views)
Book cover: Reinforcement Learning and Optimal ControlReinforcement Learning and Optimal Control
by - Athena Scientific ,
The book considers large and challenging multistage decision problems, which can be solved by dynamic programming and optimal control, but their exact solution is computationally intractable. We discuss solution methods that rely on approximations.
(717 views)

Book cover: An Introduction to Probabilistic ProgrammingAn Introduction to Probabilistic Programming
by - arXiv.org ,
This text is designed to be a graduate-level introduction to probabilistic programming. It provides a thorough background for anyone wishing to use a probabilistic programming system, and introduces the techniques needed to build these systems.
(869 views)
Book cover: A Brief Introduction to Machine Learning for EngineersA Brief Introduction to Machine Learning for Engineers
by - arXiv.org ,
This monograph provides the starting point to the literature that every engineer new to machine learning needs. It offers a basic and compact reference that describes key ideas and principles in simple terms and within a unified treatment.
(1221 views)
Book cover: Machine Learning for Data StreamsMachine Learning for Data Streams
by - The MIT Press ,
This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA, allowing readers to try out the techniques after reading the explanations.
(1462 views)
Book cover: Elements of Causal Inference: Foundations and Learning AlgorithmsElements of Causal Inference: Foundations and Learning Algorithms
by - The MIT Press ,
This book offers a self-contained and concise introduction to causal models and how to learn them from data. The book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from data ...
(1276 views)
Book cover: Machine Learning for DesignersMachine Learning for Designers
by - O'Reilly Media ,
This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.
(1985 views)
Book cover: The Future of Machine IntelligenceThe Future of Machine Intelligence
by - O'Reilly Media ,
The series of interviews in this exclusive report unpack concepts and innovations that represent the frontiers of ever-smarter machines. You’ll get a rare glimpse into this exciting field through the eyes of some of its leading minds.
(2049 views)
Book cover: Boosting: Foundations and AlgorithmsBoosting: Foundations and Algorithms
by - The MIT Press ,
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics.
(1966 views)
Book cover: Optimal and Learning Control for Autonomous RobotsOptimal and Learning Control for Autonomous Robots
by - arXiv.org ,
The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible.
(1646 views)
Book cover: Modeling Agents with Probabilistic ProgramsModeling Agents with Probabilistic Programs
by - AgentModels.org ,
This book describes and implements models of rational agents for (PO)MDPs and Reinforcement Learning. One motivation is to create richer models of human planning, which capture human biases. The book assumes basic programming experience.
(1724 views)
Book cover: Statistical Foundations of Machine LearningStatistical Foundations of Machine Learning
by - OTexts ,
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice.
(4275 views)
Book cover: Statistical Learning and Sequential PredictionStatistical Learning and Sequential Prediction
by - University of Pennsylvania ,
This text focuses on theoretical aspects of Statistical Learning and Sequential Prediction. The minimax approach, which we emphasize throughout the course, offers a systematic way of comparing learning problems. We will discuss learning algorithms...
(2282 views)
Book cover: Understanding Machine Learning: From Theory to AlgorithmsUnderstanding Machine Learning: From Theory to Algorithms
by - Cambridge University Press ,
This book introduces machine learning and the algorithmic paradigms it offers. It provides a theoretical account of the fundamentals underlying machine learning and mathematical derivations that transform these principles into practical algorithms.
(3410 views)
Book cover: Lecture Notes in Machine LearningLecture Notes in Machine Learning
by - Central Connecticut State University ,
Contents: Introduction; Concept learning; Languages for learning; Version space learning; Induction of Decision trees; Covering strategies; Searching the generalization / specialization graph; Inductive Logic Progrogramming; Unsupervised Learning ...
(4842 views)
Book cover: Machine Learning and Data Mining: Lecture NotesMachine Learning and Data Mining: Lecture Notes
by - University of Toronto ,
Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.
(4906 views)
Book cover: Learning Deep Architectures for AILearning Deep Architectures for AI
by - Now Publishers ,
This book discusses the principles of learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models.
(3002 views)
Book cover: An Introduction to Statistical LearningAn Introduction to Statistical Learning
by - Springer ,
This book provides an introduction to statistical learning methods. It contains a number of R labs with detailed explanations on how to implement the various methods in real life settings and it is a valuable resource for a practicing data scientist.
(4816 views)
Book cover: Algorithms for Reinforcement LearningAlgorithms for Reinforcement Learning
by - Morgan and Claypool Publishers ,
We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.
(3398 views)
Book cover: A Survey of Statistical Network ModelsA Survey of Statistical Network Models
by - arXiv ,
We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.
(3459 views)
Book cover: Machine Learning: The Complete GuideMachine Learning: The Complete Guide
- Wikipedia ,
Contents: Introduction and Main Principles; Background and Preliminaries; Knowledge discovery in Databases; Reasoning; Search Methods; Statistics; Main Learning Paradigms; Classification Tasks; Online Learning; Semi-supervised learning; etc.
(6950 views)
Book cover: Introduction to Machine LearningIntroduction to Machine Learning
by - Cambridge University Press ,
Over the past two decades Machine Learning has become one of the mainstays of information technology and a rather central part of our life. Smart data analysis will become even more pervasive as a necessary ingredient for technological progress.
(3914 views)
Book cover: An Introductory Study on Time Series Modeling and ForecastingAn Introductory Study on Time Series Modeling and Forecasting
by - arXiv ,
This work presents a concise description of some popular time series forecasting models used in practice, with their features. We describe three important classes of time series models, viz. the stochastic, neural networks and SVM based models.
(6309 views)
Book cover: The LION Way: Machine Learning plus Intelligent OptimizationThe LION Way: Machine Learning plus Intelligent Optimization
by - Lionsolver, Inc. ,
Learning and Intelligent Optimization (LION) is the combination of learning from data and optimization applied to solve complex problems. This book is about increasing the automation level and connecting data directly to decisions and actions.
(19114 views)
Book cover: A Course in Machine LearningA Course in Machine Learning
by - ciml.info ,
Tis is a set of introductory materials that covers most major aspects of modern machine learning (supervised and unsupervised learning, large margin methods, probabilistic modeling, etc.). It's focus is on broad applications with a rigorous backbone.
(11281 views)
Book cover: A First Encounter with Machine LearningA First Encounter with Machine Learning
by - University of California Irvine ,
The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A prelude to the more advanced text books.
(5067 views)
Book cover: Bayesian Reasoning and Machine LearningBayesian Reasoning and Machine Learning
by - Cambridge University Press ,
The book is designed for final-year undergraduate students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basics to advanced techniques within the framework of graphical models.
(14767 views)
Book cover: Introduction to Machine LearningIntroduction to Machine Learning
by - arXiv ,
Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).
(16240 views)
Book cover: Reinforcement LearningReinforcement Learning
by - InTech ,
This book describes and extends the scope of reinforcement learning. It also shows that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional controllers.
(15164 views)
Book cover: Machine LearningMachine Learning
by - InTech ,
Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, and more.
(10710 views)
Book cover: Reinforcement Learning: An IntroductionReinforcement Learning: An Introduction
by - The MIT Press ,
The book provides a clear and simple account of the key ideas and algorithms of reinforcement learning. It covers the history and the most recent developments and applications. The only necessary mathematical background are concepts of probability.
(18782 views)
Book cover: Gaussian Processes for Machine LearningGaussian Processes for Machine Learning
by - The MIT Press ,
Gaussian processes provide a principled, practical, probabilistic approach to learning in kernel machines. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics.
(20635 views)
Book cover: Machine Learning, Neural and Statistical ClassificationMachine Learning, Neural and Statistical Classification
by - Ellis Horwood ,
The book provides a review of different approaches to classification, compares their performance on challenging data-sets, and draws conclusions on their applicability to realistic industrial problems. A wide variety of approaches has been taken.
(19530 views)
Book cover: Introduction To Machine LearningIntroduction To Machine Learning
by ,
This book concentrates on the important ideas in machine learning, to give the reader sufficient preparation to make the extensive literature on machine learning accessible. The author surveys the important topics in machine learning circa 1996.
(20137 views)
Book cover: Inductive Logic Programming: Theory and MethodsInductive Logic Programming: Theory and Methods
by - ScienceDirect ,
Inductive Logic Programming is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. The authors survey the most important theories and methods of this new field.
(25888 views)
Book cover: Practical Artificial Intelligence Programming in JavaPractical Artificial Intelligence Programming in Java
by - Lulu.com ,
The book uses the author's libraries and the best of open source software to introduce AI (Artificial Intelligence) technologies like neural networks, genetic algorithms, expert systems, machine learning, and NLP (natural language processing).
(17473 views)
Book cover: Information Theory, Inference, and Learning AlgorithmsInformation Theory, Inference, and Learning Algorithms
by - Cambridge University Press ,
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
(19670 views)