English | 2022 | ISBN: 1681089688 | 232 pages | True PDF EPUB | 22.82 MB
This book is a review of recent artificial intelligence approaches, initiatives and applications in engineering and science fields. It features contributions that highlight the use of techniques such as machine learning, mining engineering, modeling and simulation, and fuzzy logic methods in the fields of communication, networking and information engineering.
The collection of chapters should inspire scholars involved in theoretical and applied sciences to contribute to research using computational intelligence principles and methods in their respective research communities. Professionals working on systems engineering, communications, innovative computing systems and adaptive technologies for sustainable growth, will also be able to benefit from the information provided in the book.

English | 2022 | ISBN: 1647824192 | 287 pages | True PDF | 8.38 MB
Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines can help you prepare.
Artificial intelligence (AI) has impacted many industries around the world—banking and finance, pharmaceuticals, automotive, medical technology, manufacturing, and retail. But it has only just begun its odyssey toward cheaper, better, and faster predictions that drive strategic business decisions. When prediction is taken to the max, industries transform, and with such transformation comes disruption.

English | 2023 | ISBN: 978-1394174102 | 323 pages | True PDF EPUB | 7.62 MB
Prepare for the coming convergence of AI and quantum computing
A collection of essays from 20 renowned, international authors working in industry, academia, and government, Convergence: Artificial Intelligence and Quantum Computing explains the impending convergence of artificial intelligence and quantum computing. A diversity of viewpoints is presented, each offering their view of this coming watershed event.

English | 2022 | ISBN: 1683922239 | 739 pages | True PDF | 69.35 MB
Features
+Includes new chapters on deep learning, AI security, and AI programming

English | 2022 | ISBN: 0470647507 | 339 pages | True PDF | 43.43 MB
Artificial Intelligence in Digital Holographic Imaging Technical Basis and Biomedical Applications An eye-opening discussion of 3D optical sensing, imaging, analysis, and pattern recognition Artificial intelligence (AI) has made great progress in recent years. Digital holographic imaging has recently emerged as a powerful new technique well suited to explore cell structure and dynamics with a nanometric axial sensitivity and the ability to identify new cellular biomarkers. By combining digital holography with AI technology, including recent deep learning approaches, this system can achieve a record-high accuracy in non-invasive, label-free cellular phenotypic screening. It opens up a new path to data-driven diagnosis. Artificial Intelligence in Digital Holographic Imaging introduces key concepts and algorithms of AI to show how to build intelligent holographic imaging systems drawing on techniques from artificial neural networks, convolutional neural networks, and generative adversarial network. Readers will be able to gain an understanding of the basics for implementing AI in holographic imaging system designs and connecting practical biomedical questions that arise from the use of digital holography with various AI algorithms in intelligence models. What's Inside Introductory background on digital holography Key concepts of digital holographic imaging Deep-learning techniques for holographic imaging AI techniques in holographic image analysis Holographic image-classification models Automated phenotypic analysis of live cells For readers with various backgrounds, this book provides a detailed discussion of the use of intelligent holographic imaging system in biomedical fields with great potential for biomedical application.
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English | 2023 | ISBN: 978-3110761993 | 298 pages | True PDF EPUB | 98.26 MB
THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS
By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Muller V Philosophy and Theory of Artificial Intelligence 2021 | 4.08 MB
N/A | 244 Pages

Title: N/A
Author: N/A
Year: N/A

Released: 3/2018
Duration: 1h 17m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 1.44 GB
Level: Beginner | Genre: eLearning | Language: English
Machine learning is one of the liveliest areas in artificial intelligence. Machine learning algorithms allow computers to learn new things without being programmed. They use statistics as a way to better understand the massive amounts of data that we create every day. These newer algorithms help machines classify images, sounds, and videos. They can answer our questions, discover new drugs, and even write songs. In this course, we review the definition and types of machine learning: supervised, unsupervised, and reinforcement. Then you can see how to use popular algorithms such as decision trees, clustering, and regression analysis to see patterns in your massive data sets. Finally you can learn about some of the pitfalls when starting out with machine learning.

Put the Art in Artificial Intelligence: Create stunning Digital Art in seconds
Content Source:https://www.skillshare.com/en/classes/Put-the-Art-in-Artificial-Intelligence-Create-stunning-Digital-Art-in-seconds/1726001685?via=search-layout-grid
Genre / Category:Photography
File Size :964MB

Published 9/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.08 GB | Duration: 1h 40m
Learn to build & code AI models using Scratch