Subcategories

Nuclear Reactor Engineering: Reactor Systems Engineering

Posted By: AvaxGenius
Nuclear Reactor Engineering: Reactor Systems Engineering

Nuclear Reactor Engineering: Reactor Systems Engineering by Samuel Glasstone
English | PDF | 1994 | 395 Pages | ISBN : 1461358663 | 35.85 MB

Dr. Samuel Glasstone, the senior author of the previous editions of this book, was anxious to live until his ninetieth birthday, but passed away in 1986, a few months short of this milestone. I am grateful for the many years of stimulation received during our association, and in preparing this edition have attempted to maintain his approach.

Communications, Signal Processing, and Systems

Posted By: AvaxGenius
Communications, Signal Processing, and Systems

Communications, Signal Processing, and Systems: Proceedings of the 8th International Conference on Communications, Signal Processing, and Systems by Qilian Liang
English | PDF,EPUB | 2020 | 2719 Pages | ISBN : 9811394083 | 394.39 MB

This book brings together papers from the 2019 International Conference on Communications, Signal Processing, and Systems, which was held in Urumqi, China, on July 20–22, 2019. Presenting the latest developments and discussing the interactions and links between these multidisciplinary fields, the book spans topics ranging from communications to signal processing and systems. It is chiefly intended for undergraduate and graduate students in electrical engineering, computer science and mathematics, researchers and engineers from academia and industry, as well as government employees.

NEURAL NETWORKS with MATLAB [Repost]

Posted By: tanas.olesya
NEURAL NETWORKS with MATLAB [Repost]

NEURAL NETWORKS with MATLAB by Marvin L.
English | 2016 | ISBN: 1539701956 | 418 pages | PDF | 2.05 Mb

Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications

Posted By: AvaxGenius
Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications

Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications by Jonas Mockus
English | PDF | 1997 | 394 Pages | ISBN : 0792343271 | 23.92 MB

Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems, especially those of large scale for which exact optimization approaches can be prohibitively costly. The book covers all aspects ranging from the formal presentation of the Bayesian Approach, to its extension to the Bayesian Heuristic Strategy, and its utilization within the informal, interactive Dynamic Visualization strategy.

Deep Learning in Mining of Visual Content

Posted By: AvaxGenius
Deep Learning in Mining of Visual Content

Deep Learning in Mining of Visual Content by Akka Zemmari
English | PDF(Repost),EPUB | 2020 | 117 Pages | ISBN : 3030343758 | 10.76 MB

This book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning. It contains chapters which introduce theoretical and mathematical foundations of neural networks and related optimization methods. Then it discusses some particular very popular architectures used in the domain: convolutional neural networks and recurrent neural networks.

Neural Networks and Analog Computation: Beyond the Turing Limit

Posted By: AvaxGenius
Neural Networks and Analog Computation: Beyond the Turing Limit

Neural Networks and Analog Computation: Beyond the Turing Limit by Hava T. Siegelmann
English | PDF | 1999 | 193 Pages | ISBN : 0817639497 | 16 MB

The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models.

Soft Computing for Problem Solving 2019: Proceedings of SocProS 2019, Volume 2

Posted By: AvaxGenius
Soft Computing for Problem Solving 2019: Proceedings of SocProS 2019, Volume 2

Soft Computing for Problem Solving 2019: Proceedings of SocProS 2019, Volume 2 by Atulya K. Nagar
English | PDF | 2020 | 223 Pages | ISBN : 9811532869 | 8.38 MB

This book features the outcomes of the 9th International Conference on Soft Computing for Problem Solving, SocProS 2019, which brought together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to identify potential future directions.

Building Recommender Systems with Machine Learning and AI [Updated 4/2/2020]

Posted By: IrGens
Building Recommender Systems with Machine Learning and AI [Updated 4/2/2020]

Building Recommender Systems with Machine Learning and AI [Updated 4/2/2020]
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 9h 5m | 1.6 GB
Instructor: Frank Kane

Neural Advances in Processing Nonlinear Dynamic Signals (Repost)

Posted By: AvaxGenius
Neural Advances in Processing Nonlinear Dynamic Signals (Repost)

Neural Advances in Processing Nonlinear Dynamic Signals by Anna Esposito
English | PDF,EPUB | 2018 (2019 Edition) | 313 Pages | ISBN : 3319950975 | 19.01 MB

This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community.

Using Artificial Neural Networks for Analog Integrated Circuit Design Automation

Posted By: AvaxGenius
Using Artificial Neural Networks for Analog Integrated Circuit Design Automation

Using Artificial Neural Networks for Analog Integrated Circuit Design Automation by João P. S. Rosa
English | EPUB | 2020 | 117 Pages | ISBN : 3030357422 | 4.03 MB

This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices’ sizes to circuits’ performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices’ sizes.

Advanced Information Networking and Applications

Posted By: AvaxGenius
Advanced Information Networking and Applications

Advanced Information Networking and Applications: Proceedings of the 34th International Conference on Advanced Information Networking and Applications (AINA-2020) by Leonard Barolli
English | PDF | 2020 | 1535 Pages | ISBN : 3030440400 | 122.04 MB

This proceedings book covers the theory, design and applications of computer networks, distributed computing and information systems. Today’s networks are evolving rapidly, and there are several developing areas and applications. These include heterogeneous networking supported by recent technological advances in power wireless communications, along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations, which is emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enables novel, low-cost and high-volume applications.

Data Manipulation in Python: A Pandas Crash Course

Posted By: IrGens
Data Manipulation in Python: A Pandas Crash Course

Data Manipulation in Python: A Pandas Crash Course
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 8h 47m | 3.11 GB
Instructors: Samuel Hinton, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team

Practical Deep Learning on the Cloud

Posted By: IrGens
Practical Deep Learning on the Cloud

Practical Deep Learning on the Cloud
.MP4, AVC, 1920x1080, 30 fps | English, AAC, 2 Ch | 2h 27m | 1.44 GB
Instructor: Rustem Feyzkhanov

Complex Networks and Their Applications VIII (Repost)

Posted By: AvaxGenius
Complex Networks and Their Applications VIII (Repost)

Complex Networks and Their Applications VIII: Volume 2 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019 by Hocine Cherifi
English | True EPUB | 2020 | 1047 Pages | ISBN : 3030366820 | 80.43 MB

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, and network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.

C# Machine Learning Projects: Nine real-world projects to build robust and high-performing machine learning models with C#

Posted By: IrGens
C# Machine Learning Projects: Nine real-world projects to build robust and high-performing machine learning models with C#

C# Machine Learning Projects: Nine real-world projects to build robust and high-performing machine learning models with C# by Yoon Hyup Hwang
English | June 18, 2018 | ISBN: 1788996402 | PDF | 350 pages | 11 MB