Python Deep Learning Algorithm (17 results)

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paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2023-12 Pages: 424 Publisher: Tsinghua University Press This book comprehensively introduces the knowledge of deep meta-learning technology. including meta-learning. machine learning. deep learning and its technical platform and application cases. provides a relatively complete deep meta-learning framework. and proposes some inspiring meta-learning algorithms and thinking directions based on the research results of the author's research group. The book ha.

paperback. Condition: New. Paperback. Pub Date: 2024-05 Pages: 208 Publisher: Tsinghua University Press This book introduces how to build a system by yourself from four levels: basic methods. popular methods. optimal methods and new technologies. Through the study of this book. readers can master the basic concepts of the system. understand different types of engines and their functions. learn to use traditional algorithms to build systems and hybrid systems. and use clustering and classification algorithms to build ma.

paperback. Condition: New. Language:Chinese.Paperback.Pub Date:2022-06-01 Pages:448 Publisher:China Water Resources and Hydropower Press Machine Learning Deep Learning Image Recognition from Basics to Case Practice introduces the field of artificial intelligence with a large number of graphics and images combined with Python code Knowledge about image recognition. The book consists of 3 parts. of which the first part introduces the basic knowledge and the use of related tools such as Python. Jupyter Nobebook and NumPy.

paperback. Condition: New. Paperback. Pub Date: 2023-06 Pages: 396 Publisher: China Water Resources and Hydropower Press This book is divided into 8 chapters. The main contents include mathematical knowledge related to artificial intelligence. syntax and techniques unique to the Python language. the implementation of transparent and seamless release of Docker models. the industry's excellent Git code version management tool. the configuration of the model development environment. IDE development tools commonly used by .

paperback. Condition: New. Paperback. Pub Date: 2020-09-01 Publisher: China Water Resources and Hydropower Press Illustrated Machine Learning-Algorithm Principles and Implementation of Python Language Starting from the application scenario. using a combination of a large number of diagrams and flowcharts to explain the basic knowledge of machine learning And the application of commonly used classic algorithms. the whole book does not have a large theoretical introduction and complex mathematical formula derivation. nor.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2022-07-01 Pages: 298 Publisher: China Water Conservancy and Hydropower Publishing House Intelligent Recommendation System Development Practice is written based on Python 3.7. The whole book focuses on the development practice of the recommendation model. and introduces various types of recommendations for readers. The development process of the model and its application in various business scenarios. The book is divided into 4 parts. The first part brief.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2022-09-01 Pages: 340 Publisher: China Water Conservancy and Hydropower Press Deep learning is one of the most popular fields of artificial intelligence. Methods of implementing various algorithms. and the mathematics behind the algorithms. The book is divided into 3 parts with a total of 11 chapters. of which the first part introduces the relevant knowledge of getting started with deep learning. how to build your own neural network. and how to use Python.

paperback. Condition: New. Language:Chinese.Paperback.Pub Date:2022-06-01 Pages:448 Publisher:China Water Resources and Hydropower Press Machine Learning Deep Learning Image Recognition from Basics to Case Practice introduces the field of artificial intelligence with a large number of graphics and images combined with Python code Knowledge about image recognition. The book consists of 3 parts. of which the first part introduces the basic knowledge and the use of related tools such as Python. Jupyter Nobebook and NumPy.

paperback. Condition: New. Language:Chinese.PAPERBACK. PUB DATE: 2020-08-01 Pub Date: 2020-08-01 Publisher: Southeast University Press Python Deep Learning Algorithm Practice (Copy Edition) in-depth analysis of the principles and related technologies of deep learning. The book uses Python from the basic mathematical knowledge. led the reader to create a classic depth learning network from zero. so that the reader gradually understands deep learning in this process. .

paperback. Condition: New. Paperback. Pub Date: 2020-04-01 Pages: 232 Publisher: Mechanical Industry Press Face Recognition and Beauty Algorithm: Based on Python. Machine Learning and Deep Learning is a book for beginners to get started with artificial intelligence image processing technology. The main purpose of the book is to lead readers to learn about face recognition and beauty algorithms from scratch.?The book introduces the relevant knowledge of Python image processing. machine learning and deep learning theory .

paperback. Condition: New. Paperback. Pub Date: 2020-07-01 Pages: 374 Publisher: Machinery Industry Press Machine learning is an extremely important research direction in the field of artificial intelligence. and deep learning is a branch of machine learning that is very close to AI. The idea lies in Establish a neural network for analysis and learning. imitate the way the human brain perceives and organize. and make decisions based on input data.?In the process of rapid development of deep learning. related products a.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The present study developed an autonomous algorithm for the Convective cell Identification and TRAcking (CITRA) using DWR reflectivity images. The CITRA algorithm is implemented in Python using Deep learning technique of Neural Networks. Optical Character Recognition is used in the present study through 'Tesseract' which is an unsupervised Neural Network module based on LSTM which analyses the input dimensional pixel array/image and outputs high-level strings. The algorithm runs through the DWR reflectivity image pixel values and recognizes the intensities of the pixels (>=30 dB) and segregates convective cells along with other estimated cell properties such as centroid of the storm, the area covered, distance and direction from the radar centre. The performance of CITRA algorithm was tested on different convective storms and it could successfully identify and track them along with other physical properties of the convective cells. Further, we have demonstrated the potential application of CITRA algorithm on the evolution of convective cells detected within the radar range. Presently, CITRA algorithm takes only reflectivity images as a single input parameter.