Автор: Eshkabilov Sulaymon L. Название: Practical MATLAB Modeling with Simulink: Programming and Simulating Ordinary and Partial Differential Equations ISBN: 1484257987 ISBN-13(EAN): 9781484257982 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Part I: Ordinary Differential EquationsChapter 1: Analytical Solutions of Ordinary Differential EquationsChapter 2: Numerical Methods for First Order ODEsChapter 3: Numerical Methods for Second Order ODEsChapter 4: Stiff ODEsChapter 5: Higher Order and Coupled ODEsChapter 6: Implicit ODEsChapter 7: Comparative Analysis of ODE Solution MethodsPart II: Ordinary Differential Equations-Boundary Value ProblemsChapter 8: Boundary Value ProblemsPart III: Applications of Ordinary Differential EquationsChapter 9: Spring-Mass-Damper SystemsChapter 10: Electro-Mechanical and Mechanical SystemsChapter 11: Trajectory ProblemsChapter 12: Simulation ProblemsPart IV: Partial Differential EquationsChapter 13: Solving Partial Differential Equations
Автор: Layla S. Mayboudi Название: Practical Heat Transfer: Using MATLAB and COMSOL ISBN: 1683926331 ISBN-13(EAN): 9781683926337 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 79470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Guides the reader through the subject of heat transfer, covering the analytical, coding, finite element, and hybrid methods of thermal modelling. The book leads the reader through the processes of model creation for heat transfer analysis and validating them using analytical techniques and partial differential equations.
Автор: Attaway, Stormy Название: MATLAB ISBN: 0128154799 ISBN-13(EAN): 9780128154793 Издательство: Elsevier Science Рейтинг: Цена: 55950.00 T Наличие на складе: Нет в наличии. Описание: MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and built-in functions to easily exploit MATLAB's extensive capabilities for tackling engineering and scientific problems. Assuming no knowledge of programming, this book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. The fifth edition has been updated to reflect the functionality of the current version of MATLAB (R2018a), including the addition of local functions in scripts, the new string type, coverage of recently introduced functions to import data from web sites, and updates to the Live Editor and App Designer.
Автор: Irfan Turk Название: Practical MATLAB ISBN: 1484252802 ISBN-13(EAN): 9781484252802 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Apply MATLAB programming to the mathematical modeling of real-life problems from a wide range of topics. This pragmatic book shows you how to solve your programming problems, starting with a brief primer on MATLAB and the fundamentals of the MATLAB programming language. Then, you’ll build fully working examples and computational models found in the financial, engineering, and scientific sectors. As part of this section, you’ll cover signal and image processing, as well as GUIs.
After reading and using Practical MATLAB and its accompanying source code, you’ll have the practical know-how and code to apply to your own MATLAB programming projects.
What You Will Learn
Discover the fundamentals of MATLAB and how to get started with it for problem solvingApply MATLAB to a variety of problems and case studiesCarry out economic and financial modeling with MATLAB, including option pricing and compound interestUse MATLAB for simulation problems such as coin flips, dice rolling, random walks, and traffic flowsSolve computational biology problems with MATLABImplement signal processing with MATLAB, including currents, Fast Fourier Transforms (FFTs), and harmonic analysisProcess images with filters and edge detectionBuild applications with GUIs
Who This Book Is For
People with some prior experience with programming and MATLAB.
Discover The Incredible World Of Machine Learning With This Amazing Guide
Have you come across the terms machine learning and neural networks in most articles you have recently read? Do you also want to learn how to build a machine learning model that will answer your questions within a blink of your eyes? If you responded yes to any of the above questions, you have come to the right place.
Machine learning and artificial intelligence have been used in different machines and applications to improve the user's experience. One can also use machine learning to make data analysis and predicting the output for some data sets easy. All you need to do is choose the right algorithm, train the model and test the model before you apply it on any real-world tool. It is that simple isn't it?
Apart from this, you will also learn more about:
The Different Types Of Learning Algorithm That You Can Expect To Encounter
The Numerous Applications Of Machine Learning And Deep Learning
The Best Practices For Picking Up Neural Networks
What Are The Best Languages And Libraries To Work With
The Various Problems That You Can Solve With Machine Learning Algorithms
And much more...
Well, you can do it faster if you use Python. This language has made it easy for any user, even an amateur, to build a strong machine learning model since it has numerous directories and libraries that make it easy for one to build a model. Do you want to know how to build a machine learning model and a neural network?
So, what are you waiting for? Grab a copy of this book now
Автор: Seneque Gareth, Chua Darrell Название: Hands-On Deep Learning with Go ISBN: 1789340993 ISBN-13(EAN): 9781789340990 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using ...
Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms.
For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model.
After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads.
This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production.
What You Will Learn
Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using PythonFollow a deep learning project from conception to production using TensorFlowUse NumPy with Kivy to build cross-platform data science applications
Who This Book Is For
Data scientists, machine learning and deep learning engineers, software developers.
Автор: Lapan Maxim Название: Deep Reinforcement Learning Hands-On - Second Edition ISBN: 1838826998 ISBN-13(EAN): 9781838826994 Издательство: Неизвестно Рейтинг: Цена: 98080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: With six new chapters, Deep Reinforcement Learning Hands-On Second edition is completely updated and expanded with the very latest reinforcement learning (RL) tools and techniques, providing you with an introduction to RL, as well as the hands-on ability to code intelligent learning agents to perform a range of practical tasks.
Автор: Fernбndez Villбn Alberto Название: Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3 ISBN: 1789344913 ISBN-13(EAN): 9781789344912 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Mastering OpenCV 4 with Python is a comprehensive guide to help you to get acquainted with various computer vision algorithms running in real-time. This book will help you to build complete projects on image processing, motion detection, and image segmentation where you can gain advanced computer vision techniques.
Автор: Rivera, Juan De Dios Santos Название: Practical tensorflow.js ISBN: 1484262727 ISBN-13(EAN): 9781484262726 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web apps. The most common and accessible platform users interact with everyday is their web browser, making it an ideal environment to deploy AI systems. TensorFlow.js is a well-known and battle-tested library for creating browser solutions. Working in JavaScript, the so-called language of the web, directly on a browser, you can develop and serve deep learning applications.You'll work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis. Also, these topics are very varied in terms of the kind of data they use, their output, and the training phase. Not everything in machine learning is deep networks, there is also what some call shallow or traditional machine learning. While TensorFlow.js is not the most common place to implement these, you'll be introduce them and review the basics of machine learning through TensorFlow.js. What You'll Learn
Build deep learning products suitable for web browsers
Work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN)
Develop apps using image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis
Who This Book Is For Programmers developing deep learning solutions for the web and those who want to learn TensorFlow.js with at least minimal programming and software development knowledge. No prior JavaScript knowledge is required, but familiarity with it is helpful.
Автор: Arumugam Rajesh, Shanmugmani Rajalingappaa Название: Hands-on Natural Language Processing with Python ISBN: 178913949X ISBN-13(EAN): 9781789139495 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP challenges. The book equips you with practical knowledge to implement deep learning in your linguistic applications using NLTk and Python`s popular deep learning library, TensorFlow.
Автор: Pawlus Michael, Devine Rodger Название: Hands-On Deep Learning with R: A practical guide to designing, building, and improving neural network models using R ISBN: 1788996836 ISBN-13(EAN): 9781788996839 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Deep learning enables efficient and accurate learning from data. Developers working with R will be able to put their knowledge to work with this practical guide to deep learning. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time.
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