[PDF] Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots - eBooks Review

Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots


Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots
DOWNLOAD

Download Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page



Fundamentals Of Data Science Data Mining Machine Learning Deep Learning And Iots


Fundamentals Of Data Science Data Mining Machine Learning Deep Learning And Iots
DOWNLOAD
Author : Dr. A. SIVAKUMAR
language : en
Publisher: SK Research Group of Companies
Release Date : 2021-12-27

Fundamentals Of Data Science Data Mining Machine Learning Deep Learning And Iots written by Dr. A. SIVAKUMAR and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-27 with Computers categories.


Dr. A. SIVAKUMAR, Assistant Professor, Department of Computer Science, Rathinam College of Arts and Science, Coimbatore, Tamil Nadu. SULAIMAN AL MASWARI, SOLAF MOHAMAD, GOURAV SONONE, Department of Information Technology, Rathinam College of Arts and Science, Coimbatore, Tamil Nadu.



Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots


Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots
DOWNLOAD
Author : Dr. P. Kavitha
language : en
Publisher: Leilani Katie Publication
Release Date : 2023-12-23

Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots written by Dr. P. Kavitha and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-23 with Computers categories.


Dr. P. Kavitha, Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science, Coimbatore, Tamil Nadu, India. Mr. P. Jayasheelan, Assistant Professor, Department of Computer Science, Sri Krishna Aditya College of arts and Science, Coimbatore, Tamil Nadu, India. Ms. C. Karpagam, Assistant Professor, Department of Computer Science with Data Analytics, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, India. Dr. K. Prabavathy, Assistant Professor, Department of Data Science and Analytics, Sree Saraswathi Thyagaraja College, Pollachi, Coimbatore, Tamil Nadu, India.



Introduction To Algorithms For Data Mining And Machine Learning


Introduction To Algorithms For Data Mining And Machine Learning
DOWNLOAD
Author : Xin-She Yang
language : en
Publisher: Academic Press
Release Date : 2019-06-17

Introduction To Algorithms For Data Mining And Machine Learning written by Xin-She Yang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-17 with Mathematics categories.


Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data. Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages



Data Mining And Machine Learning


Data Mining And Machine Learning
DOWNLOAD
Author : Mohammed J. Zaki
language : en
Publisher:
Release Date : 2019-12

Data Mining And Machine Learning written by Mohammed J. Zaki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12 with Data mining categories.


New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.



Deep Learning For Coders With Fastai And Pytorch


Deep Learning For Coders With Fastai And Pytorch
DOWNLOAD
Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29

Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.


Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala



Handbook Of Research On Network Enabled Iot Applications For Smart City Services


Handbook Of Research On Network Enabled Iot Applications For Smart City Services
DOWNLOAD
Author : Reddy, K. Hemant Kumar
language : en
Publisher: IGI Global
Release Date : 2023-09-26

Handbook Of Research On Network Enabled Iot Applications For Smart City Services written by Reddy, K. Hemant Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-26 with Political Science categories.


The rapid growth of IoT and its applications in smart cities pose significant challenges for academic scholars. The increasing number of interconnected devices and the massive amounts of data they generate strain traditional networks, leading to inefficiencies and security vulnerabilities. Additionally, the centralized control plane in Software Defined Networks (SDN) presents a single point of failure, hindering network performance, while IoT devices themselves are susceptible to attacks, compromising user data and privacy. To address these pressing issues, Network-Enabled IoT Applications for Smart City Services offers a compelling solution. Edited by Dr. K. Hemant Kumar Reddy, Dr. Diptendu SinhaRoy, and Tapas Mishra, this book advocates leveraging SDN to handle high-frequency data streams effectively. It also proposes the integration of blockchain technology to enhance security and reliability in IoT applications, offering a roadmap for scholars to improve network efficiency, security, and reliability in IoT and smart city domains. With their extensive expertise, the authors provide academic scholars with a comprehensive and innovative resource that inspires further research and development in this evolving field, enabling them to make significant contributions to the advancement of IoT and smart city technologies.



Python Machine Learning For Beginners


Python Machine Learning For Beginners
DOWNLOAD
Author : Leonard Deep
language : en
Publisher:
Release Date : 2019-05-13

Python Machine Learning For Beginners written by Leonard Deep and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-13 with categories.


Are you interested to get into the programming world? Do you want to learn and understand Python and Machine Learning? Python Machine Learning for Beginners is the guide for you. Python Machine Learning for Beginners is the ultimate guide for beginners looking to learn and understand how Python programming works. Python Machine Learning for Beginners is split up into easy to learn chapters that will help guide the readers through the early stages of Python programming. It's this thought out and systematic approach to learning which makes Python Machine Learning for Beginners such a sought-after resource for those that want to learn about Python programming and about Machine Learning using an object-oriented programming approach. Inside Python Machine Learning for Beginners you will discover: An introduction to Machine Learning The main concepts of Machine Learning The basics of Python for beginners Machine Learning with Python Data Processing, Analysis, and Visualizations Case studies and much more! Throughout the book, you will learn the basic concepts behind Python programming which is designed to introduce you to Python programming. You will learn about getting started, the keywords and statements, data types and type conversion. Along with different examples, there are also exercises to help ensure that the information sinks in. You will find this book an invaluable tool for starting and mastering Machine Learning using Python. Once you complete Python Machine Learning for Beginners, you will be more than prepared to take on any Python programming. Scroll back up to the top of this page and hit BUY IT NOW to get your copy of Python Machine Learning for Beginners! You won't regret it!



Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches


Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches
DOWNLOAD
Author : K. Gayathri Devi
language : en
Publisher:
Release Date : 2024-10-04

Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches written by K. Gayathri Devi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-04 with Computers categories.


This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems.



Machine Learning Approach For Cloud Data Analytics In Iot


Machine Learning Approach For Cloud Data Analytics In Iot
DOWNLOAD
Author : Sachi Nandan Mohanty
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-14

Machine Learning Approach For Cloud Data Analytics In Iot written by Sachi Nandan Mohanty and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-14 with Computers categories.


Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.



Hands On Data Science And Python Machine Learning


Hands On Data Science And Python Machine Learning
DOWNLOAD
Author : Frank Kane
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-31

Hands On Data Science And Python Machine Learning written by Frank Kane and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-31 with Computers categories.


This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.