Machine Learning with Python: Principles and Practical Techniques, Parteek Bhatia
Автор: Zhang, Yu-Jin, Название: A selection of image understanding techniques : ISBN: 1032423455 ISBN-13(EAN): 9781032423456 Издательство: Taylor&Francis Рейтинг: Цена: 19140.00 р. Наличие на складе: Нет в наличии.
Описание: This book offers a comprehensive introduction to seven commonly used image understanding techniques in modern information technology. Readers of various levels can find suitable techniques to solve their practical problems and discover the latest development in these specific domains.
Автор: Kumar Santosh, Singh Sanjay Kumar, Singh Rishav Название: Animal Biometrics: Techniques and Applications ISBN: 9811079552 ISBN-13(EAN): 9789811079559 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Author Ankur Patel shows you how to apply unsupervised learning using two simple, production-ready Python frameworks: Scikit-learn and TensorFlow using Keras.
Автор: Rever Matthew Название: Computer Vision Projects with OpenCV and Python 3 ISBN: 178995455X ISBN-13(EAN): 9781789954555 Издательство: Неизвестно Рейтинг: Цена: 6068.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book demonstrates techniques to leverage the power of Python, OpenCV, and TensorFlow to solve problems in Computer Vision. This book also shows you how to build an application that can estimate human poses within images. You will also classify images and identify humans in videos, and then develop your own handwritten digit classifier.
Автор: Kyriakides George, G. Margaritis Konstantinos Название: Hands-On Ensemble Learning with Python ISBN: 1789612853 ISBN-13(EAN): 9781789612851 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you`ll understand how to combine different machine learning algorithms to produce more accurate results from your models.
Автор: Singh, Himanshu Название: Practical machine learning and image processing ISBN: 1484241487 ISBN-13(EAN): 9781484241486 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing.
The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools.
All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application.
What You Will Learn
Discover image-processing algorithms and their applications using PythonExplore image processing using the OpenCV libraryUse TensorFlow, scikit-learn, NumPy, and other librariesWork with machine learning and deep learning algorithms for image processingApply image-processing techniques to five real-time projects
Who This Book Is For
Data scientists and software developers interested in image processing and computer vision.
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: Carneiro,Gustavo Название: Machine Learning With Noisy Labels ISBN: 0443154414 ISBN-13(EAN): 9780443154416 Издательство: Elsevier Science Рейтинг: Цена: 14140.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives.
Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Описание: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives.
Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Автор: Dey Sandipan Название: Hands-On Image Processing with Python ISBN: 1789343739 ISBN-13(EAN): 9781789343731 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers how to use the image processing libraries in Python. It will enable you to write code snippets to implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and more. You will also be able to use machine learning and deep learning models and learn to implement them with ease.
Автор: Amit Konar; Sriparna Saha Название: Gesture Recognition ISBN: 3319622102 ISBN-13(EAN): 9783319622101 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a thorough analysis of gestural data extracted from raw images and/or range data with an aim to recognize the gestures conveyed by the data. It covers image morphological analysis, type-2 fuzzy logic, neural networks and evolutionary computation for classification of gestural data. The application areas include the recognition of primitive postures in ballet/classical Indian dances, detection of pathological disorders from gestural data of elderly people, controlling motion of cars in gesture-driven gaming and gesture-commanded robot control for people with neuro-motor disability. The book is unique in terms of its content, originality and lucid writing style. Primarily intended for graduate students and researchers in the field of electrical/computer engineering, the book will prove equally useful to computer hobbyists and professionals engaged in building firmware for human-computer interfaces. A prerequisite of high school level mathematics is sufficient to understand most of the chapters in the book. A basic background in image processing, although not mandatory, would be an added advantage for certain sections.
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