Five-Layer Intelligence of the Machine Brain: System Modelling and Simulation, Wang Wen-Feng, Chen XI, Yao Tuozhong
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 9978.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Описание: Medical Imaging and Analysis Using Intelligence Computing.- Biomedical signal processing, imaging, visualization and surgical robotics.- Computational method in taxonomy study and neural dynamics.- Intelligent medical apparatus, clinical applications and intelligent design of biochips.
Автор: Mishra Abhishek Название: Machine Learning for IOS Developers ISBN: 1119602874 ISBN-13(EAN): 9781119602873 Издательство: Wiley Рейтинг: Цена: 6018.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner
Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications.
Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models--both pre-trained and user-built--with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers:
Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics
Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming
Develop skills in data acquisition and modeling, classification, and regression.
Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS)
Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML
Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
Автор: Edward Layer; Krzysztof Tomczyk Название: Measurements, Modelling and Simulation of Dynamic Systems ISBN: 3642045871 ISBN-13(EAN): 9783642045875 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A close look at analog-to-digital systems offers insight on dynamic measurement methods in this concise introduction. The construction and properties of measurement sensors are analyzed, as these represent the primary components for all measurement systems.
Автор: Hans-Joachim Heinemann; G.E.A. Meier; K.R. Sreeniv Название: IUTAM Symposium on One Hundred Years of Boundary Layer Research ISBN: 9400797974 ISBN-13(EAN): 9789400797970 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book collects peer-reviewed lectures of the IUTAM Symposium on the 100th anniversary of Boundary Layer research. Covers classification, definition and mathematics of boundary layers; instability of boundary layers and transition; boundary layers control; turbulent boundary layers; numerical treatment and boundary layer modelling;
Автор: Toyoaki Nishida; Colette Faucher Название: Modelling Machine Emotions for Realizing Intelligence ISBN: 3642126030 ISBN-13(EAN): 9783642126031 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This research book presents recent progress in modelling and synthesizing emotional intelligence. It describes major concepts and issues underlying primitive machineries, and discusses how emotional engines might be incorporated into an intelligent system.
Автор: Edward Layer; Krzysztof Tomczyk Название: Measurements, Modelling and Simulation of Dynamic Systems ISBN: 3642424651 ISBN-13(EAN): 9783642424656 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A close look at analog-to-digital systems offers insight on dynamic measurement methods in this concise introduction. The construction and properties of measurement sensors are analyzed, as these represent the primary components for all measurement systems.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Автор: Zhang Tsinghua University Press Liyi Название: Blind Equalization in Neural Networks ISBN: 3110449625 ISBN-13(EAN): 9783110449624 Издательство: Walter de Gruyter Цена: 18586.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.
Автор: Edward Layer; Krzysztof Tomczyk Название: Signal Transforms in Dynamic Measurements ISBN: 3319365347 ISBN-13(EAN): 9783319365343 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is devoted to the analysis of measurement signals which requires specific mathematical operations like Convolution, Deconvolution, Laplace, Fourier, Hilbert, Wavelet or Z transform which are all presented in the present book.
Автор: Egon Stanewsky; J. Delery; John Fulker; Paolo de M Название: Drag Reduction by Shock and Boundary Layer Control ISBN: 3642077625 ISBN-13(EAN): 9783642077623 Издательство: Springer Рейтинг: Цена: 47377.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Concerning aircraft efficiency - relevant to the present research - a reduction in aircraft drag of 10%, a reduction in aircraft fuel consumption of 30%, and a reduction in airframe, engine and system weight of 20% are envisaged.
Want to predict what your customers want to buy without them having to tell you? Want to accurately forecast sales trends for your marketing team better than any employee could ever do? Then keep reading.
You've heard it before. The rise of artificial intelligence and how it will soon replace human beings and take away our jobs. What exactly is it capable of and how does this impact me? The real question you should be asking yourself is how can I use this to my advantage? How can I use machine learning to benefit my business and surpass my business goals? This book has the answer.
Designed for the tech novice, this book will break down the fundamentals of machine learning and what it truly means. You will learn to leverage neural networks, predictive modelling, and data mining algorithms, illustrated with real-world applications for finance, business and marketing.
Machine learning isn't just for scientists or engineers anymore. It's become accessible to anyone, and you can discover it's benefits for your business.
In Machine Learning for Beginners 2019, we will reveal:
✅ The fundamentals of machine learning.
✅ Each of the buzzwords defined
✅ 20 real-world applications of machine learning.
✅ How to predict when a customer is about to churn (and prevent it from happening).
✅ How to "upsell" to your customers and close more sales.
✅ How to deal with missing data or poor data.
✅ Where to find free datasets and libraries.
✅ Exactly which machine learning libraries you need.
✅ And much much more
I know you might be overwhelmed at this point, but I assure you this book has been designed for absolute beginners. Everything is in plain English. There is no code, so no coding experience is required. You won't walk away a machine learning god, but you will walk away with key strategies you can implement right away to improve your business.
���� If you are ready to start making big changes to your business, scroll up and click buy. ����
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