Rezaul karim (127 Ergebnisse)

Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Paperback. Zustand: New. Scala as a programming language is a highly scalable integration of object-oriented and functional programming, which makes it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to train effective machine learning models using this popular language.…

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paperback. Zustand: Very Good. Deep Learning with TensorFlow: Explore neural networks with Python This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .…

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paperback. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

Zustand: New. pp. 129.

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Digital. Zustand: New. One stop guide to implementing award-winning, and cutting-edge CNN architecturesAbout This Book. Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques. Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more. Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention modelsWho This Book Is ForThis book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected.What You Will Learn. From CNN basic building blocks to advanced concepts understand practical areas they can be applied to. Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it. Learn different algorithms that can be applied to Object Detection, and Instance Segmentation . Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy. Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more. Understand the working of generative adversarial networks and how it can create new, unseen imagesIn DetailConvolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available.Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets.Style and approachAn easy to follow concise and illustrative guide explaining the core concepts of ConvNets to help you understand, implement and deploy your CNN models quickly. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (postgraduate) from the year 2013 in the subject Sociology - Work, Profession, Education, Organisation, National Institute of Development Administration (Graduate School of Public Administration), course: PhD, language: English, abstract: The effects of globalisation on gendered division of labour, global market strategies, structural adjustment programmes, use of information technology and changing work organisation, working conditions are changed in different formats and there has been an increase of female participation in employment This change becomes more significant especially for the involvement of female workers at the workplace with a great responsibility at home for family activities. Like their male counterparts women are also earners for their families. However, they have to maintain their family activities such as caring young children, looking after ageing and disabled people that seems women have to do more than their men peers. Having realized this fact, family-friendly policies have been enacted and practised in the organization on the basis of recommendations of policy makers, researchers with an intention to utilize the women capital and play an important role in uplifting living conditions of women. These FFPs serve as the balancing between work and family live. These issues are considered as the benefit for working women with or without children who enjoy the advantage to utilise their time for family responsibilities As these are the concerns, the issue of quality of life has become a new aspect for the increase of female participation in labour force . Bangladesh is waved by the globalisation, internationalisation, pressure of donor agencies and recent change in the growth of female employment. This research has been framed to examine the causal relations between the family friendly policies and working life of women in the public sector training organizations.The population size comprises of all working women of these organizations. The study population (502) is the aggregation of elements from which the sample is selected. The Sample size selected from two strata i.e. managerial level and non-managerial (support staff) level employees are 156 and 249 respectively that calculated using the formula. This is a quantitative research where Family-friendly policies are the independent variables and working life of working women is the dependent variable. Hypotheses taken relating to the independent and dependent variables will be tested using the various statistical methods. The unit of analysis of this study is working women employed in the public sector training organizations. After getting data from the respondents, data will be analyzed using SPSS. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Essay from the year 2007 in the subject Geography / Earth Science - Physical Georgraphy, Geomorphology, Environmental Studies, University of Leeds (Leeds University Business School), course: MA HRM, language: English, abstract: Research is always conducted to find out solution(s) of a problem. There are so many factors involved in the research process from data collection to result analysis. These factors sometimes distort the result, sometimes influence the findings. But a valid and reliable result is always wanted and widely acceptable. To make the research result bias free, valid and generalised triangulation plays an important role in this area by increasing the rate of certainty and bringing neutrality. It is process of using more than one method, theory, researcher and data collection method & technique to make the research findings more valid, reliable and generalisable. …

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Essay from the year 2007 in the subject Leadership and Human Resource Management - Miscellaneous, University of Leeds (Leeds University Business School), course: MA HRM, language: English, abstract: Performance appraisal (PA) is a process of setting some targets for the individuals which they are required to achieve. Performance of individuals is evaluated by the process and good performance is acknowledged by rewarding them which may be financial rise in pay, popularly known as increment or upward movement in the hierarchy i.e. promotion. Traditionally PA is a straightforward process where the manager can only review the performance of his subordinates annually. However, in order to meet the increased expectations of employers, customer demand and better output, PA plays a crucial role for which it has become a part of a wider HRM strategy called performance management (PM). Traditional PA has some limitations that can be minimised by following multi-rater PA system. 360-degree feedback and balanced scorecard are playing important role as recent innovations in the PM system. These two tools are being widely used in both public and private organisations of developed countries like UK, USA, Germany, France; even in the public sectors in Bangladesh, Non-Government Organisations (NGOs) in particular. This paper aims at discussing the traditional PA system experienced with several problems which the new innovations such as 360 degree feedback and balanced scorecard have attempted to overcome.…

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Digital. Zustand: New. Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.About This Book. Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow. Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide. Gain real-world contextualization through some deep learning problems concerning research and applicationWho This Book Is ForThe book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.What You Will Learn. Apply deep machine intelligence and GPU computing with TensorFlow. Access public datasets and use TensorFlow to load, process, and transform the data. Discover how to use the high-level TensorFlow API to build more powerful applications. Use deep learning for scalable object detection and mobile computing. Train machines quickly to learn from data by exploring reinforcement learning techniques. Explore active areas of deep learning research and applicationsIn DetailDeep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries.Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way.You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.Style and approachThis step-by-step guide explores common, and not so common, deep neural networks, and shows how they can be exploited in the real world with complex raw data. Benefit from practical examples, and learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.…

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