Ashish mathur (92 resultados)

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Condición: New. The Supervised Learning Workshop, Second Edition (Paperback or Softback).

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Paperback. Condición: Brand New. 350 pages. 9.00x7.25x0.50 inches. In Stock.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (undergraduate) from the year 2011 in the subject Business economics - Business Management, Corporate Governance, , language: English, abstract: The employee is an individual governed by the ethics, values and perceptions and the various other forces in the environment which impact his choice of job. The individual person is facing the social pressures from the society in form of the exposure and performance. The motivations related to the behavior of the employees shape the success of the organization. The needs of the employees are both the intrinsic and the extrinsic and decide the preferences and the goals and the aspirations of the employees. These job expectations can only be fulfilled if the organization has the right strategic policies to deal. The work culture of the organization decides the experience of the employees for the achievement of goals and objectives. …

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (undergraduate) from the year 2011 in the subject Business economics - Business Management, Corporate Governance, , language: English, abstract: Stress is the basic factor impacting the organization and is the major causing of reducing theproductivity of the organizations. Stress is the basis of conflicts and violence in manyorganizations. People have problems which need to be resolved otherwise they will putnegative impact touching many dimensions of human life reducing the health and the mentalbalance. The organizational productivity will reduce and there will be problems related to thequality of work life.One of the greatest challenges facing organizations today is the ever-growing competition,the continuous increase in customer expectations and customers' subsequent demands.Moreover, customers are becoming increasingly critical of the quality of services theyexperience. In order to be successful, firms must view stress management as an essential partof their strategic process.Increased competition has forced traditional organisations to find ways to retain currentemployees and to attract customers the major task of organisations is to promote customersatisfaction and loyalty while establishing a competitive advantage a major factor oncustomer satisfaction and loyalty is the quality. Increased service quality through increasedemployee performance is a viable way for organisations to remain competitive. One strategywhich has gained momentum, in services, is the concept of quality and quality management.Quality can come from happy employees. The stress in the organisations reduces the talentsand competencies by which the employees impact the service quality.…

Paperback. Condición: New. Discover how you can supervise machine learning algorithms in Python and personalize predictive models with the help of real-world datasetsKey FeaturesExplore the fundamentals of supervised machine learning and its applicationsLearn how to label and process data correctly using Python librariesGain a comprehensive overview of different machine learning algorithms used for building prediction modelsBook DescriptionWould you like to understand how and why machine learning techniques and data analytics are spearheading enterprises globally? From analyzing bioinformatics to predicting climate change, machine learning plays an increasingly pivotal role in our society.Although the real-world applications may seem complex, this book simplifies supervised learning for beginners with a step-by-step interactive approach. Working with real-time datasets, you'll learn how supervised learning, when used with Python, can produce efficient predictive models.Starting with the fundamentals of supervised learning, you'll quickly move to understand how to automate manual tasks and the process of assessing date using Jupyter and Python libraries like pandas. Next, you'll use data exploration and visualization techniques to develop powerful supervised learning models, before understanding how to distinguish variables and represent their relationships using scatter plots, heatmaps, and box plots. After using regression and classification models on real-time datasets to predict future outcomes, you'll grasp advanced ensemble techniques such as boosting and random forests. Finally, you'll learn the importance of model evaluation in supervised learning and study metrics to evaluate regression and classification tasks.By the end of this book, you'll have the skills you need to work on your real-life supervised learning Python projects.What you will learnImport NumPy and pandas libraries to assess the data in a Jupyter NotebookDiscover patterns within a dataset using exploratory data analysisUsing pandas to find the summary statistics of a datasetImprove the performance of a model with linear regression analysisIncrease the predictive accuracy with decision trees such as k-nearest neighbor (KNN) modelsPlot precision-recall and ROC curves to evaluate model performanceWho this book is forIf you are a beginner or a data scientist who is just getting started and looking to learn how to implement machine learning algorithms to build predicting models, then this book is for you. To expedite the learning process, a solid understanding of Python programming is recommended as you'll be editing the classes or functions instead of creating from scratch.…

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Condición: New. pp. 490 2nd Edition.

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Paperback. Condición: Brand New. 326 pages. 6.14x0.70x9.21 inches. In Stock.

Paperback. Condición: New. Discover how you can supervise machine learning algorithms in Python and personalize predictive models with the help of real-world datasetsKey FeaturesExplore the fundamentals of supervised machine learning and its applicationsLearn how to label and process data correctly using Python librariesGain a comprehensive overview of different machine learning algorithms used for building prediction modelsBook DescriptionWould you like to understand how and why machine learning techniques and data analytics are spearheading enterprises globally? From analyzing bioinformatics to predicting climate change, machine learning plays an increasingly pivotal role in our society.Although the real-world applications may seem complex, this book simplifies supervised learning for beginners with a step-by-step interactive approach. Working with real-time datasets, you'll learn how supervised learning, when used with Python, can produce efficient predictive models.Starting with the fundamentals of supervised learning, you'll quickly move to understand how to automate manual tasks and the process of assessing date using Jupyter and Python libraries like pandas. Next, you'll use data exploration and visualization techniques to develop powerful supervised learning models, before understanding how to distinguish variables and represent their relationships using scatter plots, heatmaps, and box plots. After using regression and classification models on real-time datasets to predict future outcomes, you'll grasp advanced ensemble techniques such as boosting and random forests. Finally, you'll learn the importance of model evaluation in supervised learning and study metrics to evaluate regression and classification tasks.By the end of this book, you'll have the skills you need to work on your real-life supervised learning Python projects.What you will learnImport NumPy and pandas libraries to assess the data in a Jupyter NotebookDiscover patterns within a dataset using exploratory data analysisUsing pandas to find the summary statistics of a datasetImprove the performance of a model with linear regression analysisIncrease the predictive accuracy with decision trees such as k-nearest neighbor (KNN) modelsPlot precision-recall and ROC curves to evaluate model performanceWho this book is forIf you are a beginner or a data scientist who is just getting started and looking to learn how to implement machine learning algorithms to build predicting models, then this book is for you. To expedite the learning process, a solid understanding of Python programming is recommended as you'll be editing the classes or functions instead of creating from scratch.…

Condición: New. Shilpi Harnal is an Associate Professor in the Department of Computer Science &amp Engineering at Chandigarh University, Mohali, Punjab, India. She specializes in cloud computing and security. She has worked on fog computing, underwater.

Taschenbuch. Condición: Neu. Measuring & Managing Customer Satisfaction In Non-star Accommodations | A Case Study Of Jodhpur (India) | Ashish Mathur | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659121227 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Taschenbuch. Condición: Neu. Neuware - Cloud and Fog Optimization-based Solutions for Sustainable Developments discusses the integration of fog computing and the Internet of Things to provide scalable, secure, and cost-effective digital infrastructures for smart services in diverse domains: - Highlights resource management solutions for the Internet of Things devices in fog computing architectures - Discusses waste management using cloud and fog computing for sustainable development, and optimization of the Internet of Things in fog computing for fault tolerance - Covers smart surveillance and monitoring using cloud and fog computing, and energy-efficient smart healthcare - Explains energy-efficient frameworks for cloud-fog environments for sustainable development, and smart grid infrastructure using cloud and fog computing - Presents the management of metropolitan mobility for public transport and smart vehicles with cloud and fog computing The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. …