Manning publications apr 2018 (4 resultados)

Taschenbuch. Condición: Neu. Neuware - SummaryMachine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. Purchase of the print book includes a free Elektronisches Buch in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyTensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.About the BookMachine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to the money chapters: exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own. What's InsideMatching your tasks to the right machine-learning and deep-learning approachesVisualizing algorithms with TensorBoardUnderstanding and using neural networksAbout the ReaderWritten for developers experienced with Python and algebraic concepts like vectors and matrices.About the AuthorAuthor Nishant Shukla is a computer vision researcher focused on applying machine-learning techniques in robotics. Senior technical editor, Kenneth Fricklas, is a seasoned developer, author, and machine-learning practitioner.Table of ContentsPART 1 - YOUR MACHINE-LEARNING RIGA machine-learning odysseyTensorFlow essentialsPART 2 - CORE LEARNING ALGORITHMSLinear regression and beyondA gentle introduction to classificationAutomatically clustering dataHidden Markov models PART 3 - THE NEURAL NETWORK PARADIGMA peek into autoencodersReinforcement learningConvolutional neural networksRecurrent neural networksSequence-to-sequence models for chatbotsUtility landscape.…

Taschenbuch. Condición: Neu. Neuware - SummaryClassic Computer Science Problems in Swift invites readers to invest their energy in some foundational techniques that have been proven to stand the test of time. Along the way they'll learn intermediate and advanced features of the Swift programming language, a worthwhile skill in its own right.About the TechnologyDon't just learn another language. Become a better programmer instead. Today's awesome iOS apps stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills in Swift, and you'll be ready for AI, data-centric programming, machine learning, and the other development challenges that will define the next decade.About the BookClassic Computer Science Problems in Swift deepens your Swift language skills by exploring foundational coding techniques and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your 'new' problems. You'll appreciate author David Kopec's amazing ability to connect the core disciplines of computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!What's Inside- Breadth-first, depth-first, and A\* search algorithms- Constraint-satisfaction problems- Solving problems with graph algorithms- Neural networks, genetic algorithms, and more- All examples written in Swift 4.1About the ReaderFor readers comfortable with the basics of Swift.About the AuthorDavid Kopec is an assistant professor of computer science and innovation at Champlain College in Burlington, Vermont. He is an experienced iOS developer and the author of Dart for Absolute Beginners.Table of Contents- Small problems - Search problems - Constraint-satisfaction problems - Graph problems - Genetic algorithms - K-means clustering - Fairly simple neural networks - Miscellaneous problems.…

Taschenbuch. Condición: Neu. Neuware - KEY FEATURES Uses the most up to date version of Camel. New chapters on security, clustering, cloud integration, Docker,and Kubernetes. Valuable examples in Java and XML. Written by core developers of Camel. Practical, insightful and comprehensive.AUDIENCEReaders should have basic Java skills.…

Taschenbuch. Condición: Neu. Neuware -SummaryClassic Computer Science Problems in Swift invites readers to invest their energy in some foundational techniques that have been proven to stand the test of time. Along the way they'll learn intermediate and advanced features of the Swift programming language, a worthwhile skill in its own right.About the TechnologyDon't just learn another language. Become a better programmer instead. Today's awesome iOS apps stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills in Swift, and you'll be ready for AI, data-centric programming, machine learning, and the other development challenges that will define the next decade.About the BookClassic Computer Science Problems in Swift deepens your Swift language skills by exploring foundational coding techniques and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your 'new' problems. You'll appreciate author David Kopec's amazing ability to connect the core disciplines of computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!What's Inside- Breadth-first, depth-first, and A\* search algorithms- Constraint-satisfaction problems- Solving problems with graph algorithms- Neural networks, genetic algorithms, and more- All examples written in Swift 4.1About the ReaderFor readers comfortable with the basics of Swift.About the AuthorDavid Kopec is an assistant professor of computer science and innovation at Champlain College in Burlington, Vermont. He is an experienced iOS developer and the author of Dart for Absolute Beginners.Table of Contents- Small problems - Search problems - Constraint-satisfaction problems - Graph problems - Genetic algorithms - K-means clustering - Fairly simple neural networks - Miscellaneous problems 224 pp. Englisch.…