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Fully Connected
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Download or read book Fully Connected written by Mel Kettle and published by BookPOD. This book was released on 2022-06-20 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you feeling exhausted and overwhelmed? Do you feel like you have no time for yourself? Are you wondering how to regain your energy and find joy? Being a leader today is hard. We are pulled in so many directions, with big responsibilities and many livelihoods reliant on us. It may surprise you that our first responsibility is to care for ourselves. To make choices that are right for us, instead of right for others. With blurred boundaries between work and life, it can be difficult to find time for this. We’ve glorified being busy to become over-scheduled and over-committed and feel guilty about taking time for ourselves. Fully Connected is for leaders who want to take back ownership of their lives and reclaim their health and energy. On their terms. When you figure out what lights you up and how to say no to what doesn’t bring you joy, you become a better leader as you energise your co-workers, communicate with conviction and create a culture of belonging. In these pages Mel Kettle shares practical, simple and actionable ideas for you to increase your self-awareness, understand what motivates you and prioritise self-care so you can become a fully connected leader.
Download or read book Fully Connected written by Julia Hobsbawm and published by Bloomsbury Publishing. This book was released on 2017-04-20 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shortlisted for the CMI's Management Book of the Year Award 2018 and the Business Book Awards 2018 Twenty-five years after the arrival of the Internet, we are drowning in data and deadlines. Humans and machines are in fully connected overdrive - and starting to become entwined as never before. Truly, it is an Age of Overload. We can never have imagined that absorbing so much information while trying to maintain a healthy balance in our personal and professional lives could feel so complex, dissatisfying and unproductive. Something is missing. That something, Julia Hobsbawm argues in this ground-breaking book, is Social Health, a new blueprint for modern connectedness. She begins with the premise that much of what we think about healthy ways to live have not been updated any more than have most post-war modern institutions, which are themselves also struggling in the twenty-first century. In 1946, the World Health Organization defined 'health' as 'a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.' What we understood by 'social' in the middle of the last century now desperately needs an update. In Fully Connected Julia Hobsbawm takes us on a journey – often a personal one, 'from Telex to Twitter' – to illustrate how the answer to the Age of Overload can come from devising management-based systems which are both highly practical and yet intuitive, and which draw inspiration from the huge advances the world has made in tackling other kinds of health, specifically nutrition, exercise, and mental well-being. Drawing on the latest thinking in health and behavioural economics, social psychology, neuroscience, management and social network analysis, this book provides a cornucopia of case studies and ideas, to educate and inspire a new generation of managers, policymakers and anyone wanting to navigate through the rough seas of overload.
Book Synopsis TensorFlow for Deep Learning by : Bharath Ramsundar
Download or read book TensorFlow for Deep Learning written by Bharath Ramsundar and published by "O'Reilly Media, Inc.". This book was released on 2018-03-01 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines. TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms. Learn TensorFlow fundamentals, including how to perform basic computation Build simple learning systems to understand their mathematical foundations Dive into fully connected deep networks used in thousands of applications Turn prototypes into high-quality models with hyperparameter optimization Process images with convolutional neural networks Handle natural language datasets with recurrent neural networks Use reinforcement learning to solve games such as tic-tac-toe Train deep networks with hardware including GPUs and tensor processing units
Download or read book Learning TensorFlow written by Tom Hope and published by "O'Reilly Media, Inc.". This book was released on 2017-08-09 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. You’ll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you’ll know how to build and deploy production-ready deep learning systems in TensorFlow. Get up and running with TensorFlow, rapidly and painlessly Learn how to use TensorFlow to build deep learning models from the ground up Train popular deep learning models for computer vision and NLP Use extensive abstraction libraries to make development easier and faster Learn how to scale TensorFlow, and use clusters to distribute model training Deploy TensorFlow in a production setting
Book Synopsis Hands-On Neural Networks with TensorFlow 2.0 by : Paolo Galeone
Download or read book Hands-On Neural Networks with TensorFlow 2.0 written by Paolo Galeone and published by Packt Publishing Ltd. This book was released on 2019-09-18 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to developing neural network-based solutions using TensorFlow 2.0 Key FeaturesUnderstand the basics of machine learning and discover the power of neural networks and deep learningExplore the structure of the TensorFlow framework and understand how to transition to TF 2.0Solve any deep learning problem by developing neural network-based solutions using TF 2.0Book Description TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you’ll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub. By the end of this TensorFlow book, you'll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production. What you will learnGrasp machine learning and neural network techniques to solve challenging tasksApply the new features of TF 2.0 to speed up developmentUse TensorFlow Datasets (tfds) and the tf.data API to build high-efficiency data input pipelinesPerform transfer learning and fine-tuning with TensorFlow HubDefine and train networks to solve object detection and semantic segmentation problemsTrain Generative Adversarial Networks (GANs) to generate images and data distributionsUse the SavedModel file format to put a model, or a generic computational graph, into productionWho this book is for If you're a developer who wants to get started with machine learning and TensorFlow, or a data scientist interested in developing neural network solutions in TF 2.0, this book is for you. Experienced machine learning engineers who want to master the new features of the TensorFlow framework will also find this book useful. Basic knowledge of calculus and a strong understanding of Python programming will help you grasp the topics covered in this book.
Book Synopsis Machine Learning with Swift by : Oleksandr Sosnovshchenko
Download or read book Machine Learning with Swift written by Oleksandr Sosnovshchenko and published by Packt Publishing Ltd. This book was released on 2018-02-28 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease Key Features Implement effective machine learning solutions for your iOS applications Use Swift and Core ML to build and deploy popular machine learning models Develop neural networks for natural language processing and computer vision Book Description Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. What you will learn Learn rapid model prototyping with Python and Swift Deploy pre-trained models to iOS using Core ML Find hidden patterns in the data using unsupervised learning Get a deeper understanding of the clustering techniques Learn modern compact architectures of neural networks for iOS devices Train neural networks for image processing and natural language processing Who this book is for iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book.
Book Synopsis Daily Graphic by : Yaw Boadu-Ayeboafoh
Download or read book Daily Graphic written by Yaw Boadu-Ayeboafoh and published by Graphic Communications Group. This book was released on 2006-03-25 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of artificial intelligence, machine learning, and deep learning in plant breeding by : Maliheh Eftekhari
Download or read book Applications of artificial intelligence, machine learning, and deep learning in plant breeding written by Maliheh Eftekhari and published by Frontiers Media SA. This book was released on 2024-05-29 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) is an extensive concept that can be interpreted as a concentration on designing computer programs to train machines to accomplish functions like or better than hu-mans. An important subset of AI is Machine Learning (ML), in which a computer is provided with the capacity to learn its own patterns instead of the patterns and restrictions set by a human programmer, thus improving from experience. Deep Learning (DL), as a class of ML techniques, employs multilayered neural networks. The application of AI to plant science research is new and has grown significantly in recent years due to developments in calculation power, proficien-cies of hardware, and software progress. AI algorithms try to provide classifications and predic-tions. As applied to plant breeding, particularly omics data, ML as a given AI algorithm tries to translate omics data, which are intricate and include nonlinear interactions, into precise plant breeding. The applications of AI are extending rapidly and enhancing intensely in sophistication owing to the capability of rapid processing of huge and heterogeneous data. The conversion of AI techniques into accurate plant breeding is of great importance and will play a key role in the new era of plant breeding techniques in the coming years, particularly multi-omics data analysis. Advancements in plant breeding mainly depend upon developing statistical methods that harness the complicated data provided by analytical technologies identifying and quantifying genes, transcripts, proteins, metabolites, etc. The systems biology approach used in plant breeding, which integrates genomics, transcriptomics, proteomics, metabolomics, and other omics data, provides a massive amount of information. It is essential to perform accurate statistical analyses and AI methods such as ML and DL as well as optimization techniques to not only achieve an understanding of networks regulation and plant cell functions but develop high-precision models to predict the reaction of new Genetically Modified (GM) plants in special conditions. The constructed models will be of great economic importance, significantly reducing the time, labor, and instrument costs when finding optimized conditions for the bio-exploitation of plants. This Research Topic covers a wide range of studies on artificial intelligence-assisted plant breeding techniques, which contribute to plant biology and plant omics research. The relevant sub-topics include, but are not restricted to, the following: • AI-assisted plant breeding using omics and multi-omics approaches • Applying AI techniques along with multi-omics to recognize novel biomarkers associated with plant biological activities • Constructing up-to-date ML modeling and analyzing methods for dealing with omics data related to different plant growth processes • AI-assisted omics techniques in the plant defense process • Combining AI-assisted omics and multi-omics techniques using plant system biology approaches • Combining bioinformatics tools with AI approaches to analyze plant omics data • Designing cutting-edge workflow and developing innovative AI biology methods for omics data analysis
Book Synopsis Socio-Cognitive and Affective Computing by : Antonio Fernández-Caballero
Download or read book Socio-Cognitive and Affective Computing written by Antonio Fernández-Caballero and published by MDPI. This book was released on 2018-09-21 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Socio-Cognitive and Affective Computing" that was published in Applied Sciences
Book Synopsis Python Programming by : Frank Millstein
Download or read book Python Programming written by Frank Millstein and published by Frank Millstein. This book was released on 2020-09-07 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Programming With Python - 8 BOOK BUNDLE!! Deep Learning With Keras Here Is A Preview Of What You’ll Learn Here… The difference between deep learning and machine learning Deep neural networks Convolutional neural networks Building deep learning models with Keras Multi-layer perceptron network models And much more... Convolutional Neural Networks In Python Here Is A Preview Of What You’ll Learn Here… Convolutional neural networks structure How convolutional neural networks actually work Convolutional neural networks applications The importance of convolution operator How to build a simple image classification CNN And much, much more! Python Machine Learning Here Is A Preview Of What You’ll Learn Here… Basics behind machine learning techniques Most commonly used machine learning algorithms, linear and logistic regression, decision trees support vector machines, k-nearest neighbors, random forests Solving multi-clasisfication problems Data visualization with Matplotlib and data transformation with Pandas and Scikit-learn Solving multi-label classification problems And much, much more... Machine Learning With TensorFlow Here Is A Preview Of What You’ll Learn Here… What is machine learning Main uses and benefits of machine learning How to get started with TensorFlow, installing and loading data Data flow graphs and basic TensorFlow expressions Creating MNIST classifiers with one-hot transformation And much, much more... Data Analytics With Python Here Is A Preview Of What You’ll Learn Here… What is Data Analytics? Difference between data science, big data and data analytics Installing python Python data structures Pandas series and data frames And much, much more... Natural Language Processing With Python Here Is A Preview Of What You’ll Learn Here… Challenges of natural language processing How natural language processing works? Part of speech tagging N-grams Running natural language processing script And much, much more... DevOps Handbook Here Is A Preview Of What You’ll Learn Here… Issues and mistakes plaguing software development What is software development life cycle? How software development life cycle works? The origins of devops Testing and building systems tools And much, much more... DevOps Adoption Here Is A Preview Of What You’ll Learn Here… Devops definition Overcoming traditional dev and ops Devops and security integration Devops success factors Is devops right for you? And much, much more... Get this book bundle NOW and SAVE money!
Book Synopsis Practical Deep Learning by : Ronald T. Kneusel
Download or read book Practical Deep Learning written by Ronald T. Kneusel and published by No Starch Press. This book was released on 2021-03-16 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about artificial intelligence and machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math—the book will cover the rest. After an introduction to Python, you’ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance. You’ll also learn: How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines How neural networks work and how they’re trained How to use convolutional neural networks How to develop a successful deep learning model from scratch You’ll conduct experiments along the way, building to a final case study that incorporates everything you’ve learned. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.
Book Synopsis Fundamentals of Communications and Networking by : Michael G. Solomon
Download or read book Fundamentals of Communications and Networking written by Michael G. Solomon and published by Jones & Bartlett Publishers. This book was released on 2014-08-08 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today's networks are required to support an increasing array of real-time communication methods. Video chat, real-time messaging, and always-connected resources put demands on networks that were previously unimagined. The Second Edition of Fundamentals of Communications and Networking helps readers better understand today's networks and the way they support the evolving requirements of different types of organizations. It discusses the critical issues of designing a network that will meet an organization's performance needs and discusses how businesses use networks to solve business problems. Using numerous examples and exercises, this text incorporates hands-on activities to prepare readers to fully understand and design modern networks and their requirements. Key Features of the Second Edition: - Introduces network basics by describing how networks work - Discusses how networks support the increasing demands of advanced communications - Illustrates how to map the right technology to an organization's needs and business goals - Outlines how businesses use networks to solve business problems, both technically and operationally.
Book Synopsis Advances in Guidance, Navigation and Control by : Liang Yan
Download or read book Advances in Guidance, Navigation and Control written by Liang Yan and published by Springer Nature. This book was released on 2023-02-10 with total page 7455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.
Book Synopsis North San Pablo Bay Restoration and Reuse Project (North Bay Water Recycling Program) by :
Download or read book North San Pablo Bay Restoration and Reuse Project (North Bay Water Recycling Program) written by and published by . This book was released on 2010 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of the Eighth Asia International Symposium on Mechatronics by : Baoyan Duan
Download or read book Proceedings of the Eighth Asia International Symposium on Mechatronics written by Baoyan Duan and published by Springer Nature. This book was released on 2022-07-12 with total page 2195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents high-quality papers from the Eighth Asia International Symposium on Mechatronics (AISM 2021). It discusses the latest technological trends and advances in electromechanical coupling and environmental adaptability design of electronic equipment, sensing and measurement, mechatronics in manufacturing and automations, energy harvesting & storage, robotics, automation and control systems. It includes papers based on original theoretical, practical and experimental simulations, development, applications, measurements, and testing. The applications and solutions discussed in the book provide excellent reference material for future product development.
Book Synopsis Deep Learning Applications with Practical Measured Results in Electronics Industries by : Mong-Fong Horng
Download or read book Deep Learning Applications with Practical Measured Results in Electronics Industries written by Mong-Fong Horng and published by MDPI. This book was released on 2020-05-22 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.
Book Synopsis Collaborative Approach to Trade by : Francesca Romana Medda
Download or read book Collaborative Approach to Trade written by Francesca Romana Medda and published by Springer. This book was released on 2017-04-24 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book applies regional analysis to the challenges facing global investment agencies seeking to enhance trade in lagging regions. It shows how spatial interaction and agent-based modelling can be used as the basis for developing new plans and policies. An in-depth analysis of trade routes is presented, which can be used to develop policies for increasing efficiency and reducing costs. Landlocked Uganda and the sea-locked South Pacific Islands serve to illustrate the problems of covering sizable distances, accelerating export flows and improving supply chain efficiency. These examples also provide an excellent illustration of the power of regional science, from assembling data bases in difficult situations to developing and applying models of the trade system.
