The Treesearcher
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Total Pages | : 648 |
Release | : 2001 |
Genre | : Kansas |
ISBN | : |
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Author | : |
Publisher | : |
Total Pages | : 648 |
Release | : 2001 |
Genre | : Kansas |
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Author | : |
Publisher | : |
Total Pages | : 50 |
Release | : 2005 |
Genre | : Forest biomass |
ISBN | : |
Author | : Marjorie V. Cushing Falanruw |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 280 |
Release | : 2016-02-20 |
Genre | : Trees |
ISBN | : 9781530133956 |
Trees of Yap, first published in 2015 as Forest Service General Technical Report PSW-GTR-249, is an up-to-date field guide for identifying the trees found on the island of Yap, Micronesia (and applicable to much of the southern Pacific). Included are descriptions and illustrations (drawings and b/w photographs) for all recorded native trees and most introduced trees. Additional information is provided on tree distribution, status, vernacular names in Micronesia, and English names when available, plus comments on the species and their uses. Fully indexed by scientific and common name. (Note that the photographs in this edition are black-and-white rather than in color as in the original Forest Service edition.)
Author | : Sean Saito |
Publisher | : Packt Publishing Ltd |
Total Pages | : 287 |
Release | : 2018-09-29 |
Genre | : Computers |
ISBN | : 1788993225 |
Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key FeaturesImplement Q-learning and Markov models with Python and OpenAIExplore the power of TensorFlow to build self-learning modelsEight AI projects to gain confidence in building self-trained applicationsBook Description Reinforcement learning is one of the most exciting and rapidly growing fields in machine learning. This is due to the many novel algorithms developed and incredible results published in recent years. In this book, you will learn about the core concepts of RL including Q-learning, policy gradients, Monte Carlo processes, and several deep reinforcement learning algorithms. As you make your way through the book, you'll work on projects with datasets of various modalities including image, text, and video. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore technologies such as TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and even build other neural networks. By the end of this book, you will have hands-on experience with eight reinforcement learning projects, each addressing different topics and/or algorithms. We hope these practical exercises will provide you with better intuition and insight about the field of reinforcement learning and how to apply its algorithms to various problems in real life. What you will learnTrain and evaluate neural networks built using TensorFlow for RLUse RL algorithms in Python and TensorFlow to solve CartPole balancingCreate deep reinforcement learning algorithms to play Atari gamesDeploy RL algorithms using OpenAI UniverseDevelop an agent to chat with humans Implement basic actor-critic algorithms for continuous controlApply advanced deep RL algorithms to games such as MinecraftAutogenerate an image classifier using RLWho this book is for Python Reinforcement Learning Projects is for data analysts, data scientists, and machine learning professionals, who have working knowledge of machine learning techniques and are looking to build better performing, automated, and optimized deep learning models. Individuals who want to work on self-learning model projects will also find this book useful.
Author | : Michael T. Goodrich |
Publisher | : John Wiley & Sons |
Total Pages | : 722 |
Release | : 2001-10-15 |
Genre | : Computers |
ISBN | : 0471383651 |
Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as well as algorithmic design patterns and experimental methods for the engineering of algorithms. Market: Computer Scientists; Programmers.
Author | : Elizabeth Petty Bentley |
Publisher | : Genealogical Publishing Com |
Total Pages | : 816 |
Release | : 2009-02 |
Genre | : Reference |
ISBN | : 9780806317960 |
This book is the answer to the perennial question, "What's out there in the world of genealogy?" What organizations, institutions, special resources, and websites can help me? Where do I write or phone or send e-mail? Once again, Elizabeth Bentley's Address Book answers these questions and more. Now in its 6th edition, The Genealogist's Address Book gives you access to all the key sources of genealogical information, providing names, addresses, phone numbers, fax numbers, e-mail addresses, websites, names of contact persons, and other pertinent information for more than 27,000 organizations, including libraries, archives, societies, government agencies, vital records offices, professional bodies, publications, research centers, and special interest groups.
Author | : Gabriel Ferrate |
Publisher | : Springer Science & Business Media |
Total Pages | : 456 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 3642834620 |
Thirty years ago pattern recognition was dominated by the learning machine concept: that one could automate the process of going from the raw data to a classifier. The derivation of numerical features from the input image was not considered an important step. One could present all possible features to a program which in turn could find which ones would be useful for pattern recognition. In spite of significant improvements in statistical inference techniques, progress was slow. It became clear that feature derivation was a very complex process that could not be automated and that features could be symbolic as well as numerical. Furthennore the spatial relationship amongst features might be important. It appeared that pattern recognition might resemble language analysis since features could play the role of symbols strung together to form a word. This led. to the genesis of syntactic pattern recognition, pioneered in the middle and late 1960's by Russel Kirsch, Robert Ledley, Nararimhan, and Allan Shaw. However the thorough investigation of the area was left to King-Sun Fu and his students who, until his untimely death, produced most of the significant papers in this area. One of these papers (syntactic recognition of fingerprints) received the distinction of being selected as the best paper published that year in the IEEE Transaction on Computers. Therefore syntactic pattern recognition has a long history of active research and has been used in industrial applications.
Author | : I. Gupta |
Publisher | : Mercury Learning and Information |
Total Pages | : 443 |
Release | : 2020-04-06 |
Genre | : Computers |
ISBN | : 1683925068 |
This book is designed to identify some of the current applications and techniques of artificial intelligence as an aid to solving problems and accomplishing tasks. It provides a general introduction to the various branches of AI which include formal logic, reasoning, knowledge engineering, expert systems, neural networks, and fuzzy logic, etc. The book has been structured into five parts with an emphasis on expert systems: problems and state space search, knowledge engineering, neural networks, fuzzy logic, and Prolog. Features: Introduces the various branches of AI which include formal logic, reasoning, knowledge engineering, expert systems, neural networks, and fuzzy logic, etc. Includes a separate chapter on Prolog to introduce basic programming techniques in AI
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Publisher | : |
Total Pages | : 1538 |
Release | : 1985 |
Genre | : Periodicals |
ISBN | : |
Author | : Sissi Closs |
Publisher | : Springer |
Total Pages | : 381 |
Release | : 2014-11-07 |
Genre | : Computers |
ISBN | : 3319136747 |
This book constitutes the refereed proceedings of the 8th Metadata and Semantics Research Conference, MTSR 2014, held in Karlsruhe, Germany, in November 2014. The 23 full papers and 9 short papers presented were carefully reviewed and selected from 57 submissions. The papers are organized in several sessions and tracks. They cover the following topics: metadata and linked data: tools and models; (meta) data quality assessment and curation; semantic interoperability, ontology-based data access and representation; big data and digital libraries in health, science and technology; metadata and semantics for open repositories, research information systems and data infrastructure; metadata and semantics for cultural collections and applications; semantics for agriculture, food and environment.