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Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself.
Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML.
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has
Deep Learning: Methods and Applications provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2)
Discusses Open AI and Open AI Gym with relevance to Reinforcement LearningApplication of TensorFlow and Keras to Reinforcement Learning Swarm Intelligence with Python in terms of Reinforcement LearningDiscusses Google's DeepMind and the future of Reinforcement Learning
Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you're a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply
The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish
Presents research exploring the potential uses and future challenges of intelligent technological advancements and their impact in education, finance, politics, business, healthcare, and engineering. The book includes coverage on a broad range of topics, such as neuronal networks, cognitive
The Fascist Painting is a serious, rich and deeply intelligent piece of work that will radically alter the way we view culture in schools and will be a key text for anyone designing a
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning
This book is the first in-depth examination of the application of theories of space to issues of second language learning. The author outlines a new conceptual framework for researching SLA that centres on the idea of 'language learning environments' and demonstrates that where people learn
A member of the PH OD Series Organizational Learning II expands and updates the ideas and concepts of the authors' ground- breaking first book. With new examples and the most up-to-date information on the technical aspects of organizational and management theory, Argyris and Schon demonstrate how
This book defines engagement for the field of language learning and contextualizes it within existing work on the psychology of language learning and teaching. Chapters address broad substantive questions concerned with what engagement is or looks like, and how it can be theorized for the language
Concise and highly regarded, this treatment of Green's functions and their applications in science and engineering is geared toward undergraduate and graduate students with only a moderate background in ordinary differential equations and partial differential equations. The text also includes a
′Refreshing, original and full of pragmatic, evidence-based advice... In my opinion this is the best book on learning and teaching available to teachers in H.E. and F.E. today. The environment has changed so quickly over recent years and Phil Race has not only kept abreast of the changes; he is
Learning programming with one of 'the coolest applications around' algorithmic puzzles ranging from scheduling selfie time to verifying the six degrees of separation hypothesis.This book builds a bridge between the recreational world of algorithmic puzzles (puzzles that can be solved by algorithms)
When machine learning, data and AI are reshaping the human experience and forcing us to develop a new ethical intelligence, Peter Hershock gives us a new way to think about attention, presence and ethics in our changing lives by balancing Western technology with Asian philosophy. Rather than
This explanation of classic theory features many relevant essays on persons, ideas, and applications. Not only is the text organized according to introductory courses, but it is also a reference tool of enduring value. Now available in
'By far the best book on investing ever written.' -- Warren BuffettThe classic text of Benjamin Graham's seminal The Intelligent Investor has now been revised and annotated to update the timeless wisdom for today's market conditions.The greatest investment advisor of the twentieth century, Benjamin
Learning to Be Teacher Leaders examines three integrated components of strong pedagogy-assessment, planning, and instruction-within a framework emphasizing the knowledge, skills, and dispositions that can empower teachers to become teacher leaders within their schools. Combining the what, why, and
In this powerful, evocative collection, master storyteller John O'Donohue explores themes of love and loss, beginnings and
INTRODUCING THE SECOND EDITION OF MINDSTAR 2018. This revision includes a new chapter which directly addresses the transitional experience of physical 'death' itself. The primise of the entire book continues to be that this is a consciousness-evolutionary, not a terminal event. Yet because of