Advanced Data Analytics Using Python
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Advanced Data Analytics Using Python
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Author : Sayan Mukhopadhyay
language : en
Publisher: Apress
Release Date : 2018-03-29
Advanced Data Analytics Using Python written by Sayan Mukhopadhyay and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-29 with Computers categories.
Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis. After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects. What You Will Learn Work with data analysis techniques such as classification, clustering, regression, and forecasting Handle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQL Examine the different big data frameworks, including Hadoop and Spark Discover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLP Who This Book Is For Data scientists and software developers interested in the field of data analytics.
Advanced Data Analytics Using Python
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Author : Sayan Mukhopadhyay
language : en
Publisher: Apress
Release Date : 2022-11-26
Advanced Data Analytics Using Python written by Sayan Mukhopadhyay and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-26 with Computers categories.
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll Learn Build intelligent systems for enterprise Review time series analysis, classifications, regression, and clustering Explore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analytics Understand Covers design patterns in Python Who This Book Is For Data scientists and software developers interested in the field of data analytics.
Data Analytics Using Machine Learning Techniques On Cloud Platforms
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Author : Seema Rawat
language : en
Publisher: CRC Press
Release Date : 2025-09-23
Data Analytics Using Machine Learning Techniques On Cloud Platforms written by Seema Rawat and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-23 with Computers categories.
Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning (ML) and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, loud-based analytics tools and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics and e-commerce. It also addresses security challenges, privacy concerns and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics. This book: Covers supervised and unsupervised learning, including regression, clustering, classification and neural networks Discusses Hadoop, Spark, Tableau, Power BI and Splunk for analytics and visualization Examines how cloud computing enhances scalability, efficiency and automation in data analytics Showcases ML-driven solutions in e-commerce, supply chain logistics, healthcare and education This book is an essential resource for students, researchers and professionals who seek to understand and apply ML-driven cloud analytics in real-world scenarios.
Advanced Analytics With Pyspark
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Author : Akash Tandon
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-06-14
Advanced Analytics With Pyspark written by Akash Tandon and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-14 with Computers categories.
The amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming. Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection, to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing. If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis. Familiarize yourself with Spark's programming model and ecosystem Learn general approaches in data science Examine complete implementations that analyze large public datasets Discover which machine learning tools make sense for particular problems Explore code that can be adapted to many uses
Marketing Analytics Using Excel
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Author : Rahul Pratap Singh Kaurav
language : en
Publisher: SAGE Publications Limited
Release Date : 2025-03-15
Marketing Analytics Using Excel written by Rahul Pratap Singh Kaurav and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-15 with Business & Economics categories.
Marketing Analytics Using Excel is the essential introduction to data-driven marketing, which simplifies complex concepts and offers practical, real-world applications. This comprehensive yet accessible guide encourages an in-depth understanding of marketing analytics, from fundamental topics and basic Excel functions to more advanced topics such as AI and predictive analytics. Packed with practical examples and easy-to-follow, fully worked problems which demonstrate how theoretical concepts are applied in real-world situations, this book also includes: • Industry case studies from leading companies like Zappos, Amazon, Netflix, and Spotify, providing insights into how marketing analytics is applied in various industries. • Exercises, activities and discussion questions to reinforce learning. • A focus on open access tools and career prospects which encourages readers to develop further. This no-nonsense guide minimises the intimidation factor of complex formulas and instead focuses on practical, real-world applications, making it essential reading for Marketing students and anyone looking to upskill. Dr Rahul Pratap Singh Kaurav is Associate Professor at FORE School of Management, New Delhi, India. Dr Asha Thomas is an Assistant Professor at Wroclaw University of Science and Technology (WUST), Poland.
Industry 4 0 Technologies For Education
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Author : P. Kaliraj
language : en
Publisher: CRC Press
Release Date : 2022-12-27
Industry 4 0 Technologies For Education written by P. Kaliraj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Education categories.
The transformative digital technologies developed for Industry 4.0 are proving to be disruptive change drivers in higher education. Industry 4.0 technologies are forming the basis of Education 4.0. Industry 4.0 Technologies for Education: Transformative Technologies and Applications examines state-of-the-art tools and technologies that comprise Education 4.0. Higher education professionals can turn to this book to guide curriculum development aimed at helping produce the workforce for Industry 4.0. The book discusses the tools and technologies required to make Education 4.0 a reality. It covers online content creation, learning management systems, and tools for teaching, learning, and evaluating. Also covered are disciplines that are being transformed by Industry 4.0 and form the core of Education 4.0 curricula. These disciplines include social work, finance, medicine, and healthcare. Mobile technologies are critical components of Industry 4.0 as well as Education 4.0. The book looks at the roles of the Internet of Things (IoT), 5G, and cloud applications in creating the Education 4.0 environment. Highlights of the book include: Technological innovations for virtual classrooms to empower students Emerging technological advancements for educational institutions Online content creation tools Moodle as a teaching, learning, and evaluation tool Gamification in higher education A design thinking approach to developing curriculum in Education 4.0 Industry 4.0 for Service 4.0 and Research 4.0 as a framework for higher education institutions Eye-tracking technology for Education 4.0 The challenges and issues of the Internet of Things (IoT) in teaching and learning
Advanced Smart Computing Technologies In Cybersecurity And Forensics
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Author : Keshav Kaushik
language : en
Publisher: CRC Press
Release Date : 2021-12-15
Advanced Smart Computing Technologies In Cybersecurity And Forensics written by Keshav Kaushik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-15 with Computers categories.
This book addresses the topics related to artificial intelligence, the Internet of Things, blockchain technology, and machine learning. It brings together researchers, developers, practitioners, and users interested in cybersecurity and forensics. The first objective is to learn and understand the need for and impact of advanced cybersecurity and forensics and its implementation with multiple smart computational technologies. This objective answers why and how cybersecurity and forensics have evolved as one of the most promising and widely-accepted technologies globally and has widely-accepted applications. The second objective is to learn how to use advanced cybersecurity and forensics practices to answer computational problems where confidentiality, integrity, and availability are essential aspects to handle and answer. This book is structured in such a way so that the field of study is relevant to each reader’s major or interests. It aims to help each reader see the relevance of cybersecurity and forensics to their career or interests. This book intends to encourage researchers to develop novel theories to enrich their scholarly knowledge to achieve sustainable development and foster sustainability. Readers will gain valuable knowledge and insights about smart computing technologies using this exciting book. This book: • Includes detailed applications of cybersecurity and forensics for real-life problems • Addresses the challenges and solutions related to implementing cybersecurity in multiple domains of smart computational technologies • Includes the latest trends and areas of research in cybersecurity and forensics • Offers both quantitative and qualitative assessments of the topics Includes case studies that will be helpful for the researchers Prof. Keshav Kaushik is Assistant Professor in the Department of Systemics, School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. Dr. Shubham Tayal is Assistant Professor at SR University, Warangal, India. Dr. Akashdeep Bhardwaj is Professor (Cyber Security & Digital Forensics) at the University of Petroleum & Energy Studies (UPES), Dehradun, India. Dr. Manoj Kumar is Assistant Professor (SG) (SoCS) at the University of Petroleum and Energy Studies, Dehradun, India.
Handbook Of Hydroinformatics
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Author : Saeid Eslamian
language : en
Publisher: Elsevier
Release Date : 2022-11-30
Handbook Of Hydroinformatics written by Saeid Eslamian and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Technology & Engineering categories.
Classic Soft-Computing Techniques is the first volume of the three, in the Handbook of HydroInformatics series. Through this comprehensive, 34-chapters work, the contributors explore the difference between traditional computing, also known as hard computing, and soft computing, which is based on the importance given to issues like precision, certainty and rigor. The chapters go on to define fundamentally classic soft-computing techniques such as Artificial Neural Network, Fuzzy Logic, Genetic Algorithm, Supporting Vector Machine, Ant-Colony Based Simulation, Bat Algorithm, Decision Tree Algorithm, Firefly Algorithm, Fish Habitat Analysis, Game Theory, Hybrid Cuckoo–Harmony Search Algorithm, Honey-Bee Mating Optimization, Imperialist Competitive Algorithm, Relevance Vector Machine, etc. It is a fully comprehensive handbook providing all the information needed around classic soft-computing techniques. This volume is a true interdisciplinary work, and the audience includes postgraduates and early career researchers interested in Computer Science, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science, Environment Science, Natural Resources, and Chemical Engineering. - Key insights from global contributors in the fields of data management research, climate change and resilience, insufficient data problem, etc. - Offers applied examples and case studies in each chapter, providing the reader with real world scenarios for comparison. - Introduces classic soft-computing techniques, necessary for a range of disciplines.
Python For Data Analysis
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Author : Andrew Park
language : en
Publisher: Andrew Park
Release Date : 2021-04-22
Python For Data Analysis written by Andrew Park and has been published by Andrew Park this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-22 with categories.
★ 55% OFF for Bookstores! NOW at $41,97 instead of $51,97!Do you want to learn more about Data Analysis and how to master it with Python?Your Customers Will Love This Amazing Guide! Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future. Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations. With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis Pandas, Jupyter and PyTorch The 7 Python libraries that make Python one of the best choices for Data Analysis Neural Network How Data Visualization and Matplotlib can help you to understand the data you are working with. Some of the main industries that are using data to improve their business with 14 real-world applications And Much More! While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics. Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, and the most important real-world applications. Would You Like To Know More? Buy it NOW and Let Your Customers Get Addicted to This Amazing Book!
Advanced Data Science And Analytics With Python
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Author : Jesús Rogel-Salazar
language : en
Publisher: CRC Press
Release Date : 2020-05-05
Advanced Data Science And Analytics With Python written by Jesús Rogel-Salazar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-05 with Business & Economics categories.
Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences – in this case, literally to the users’ fingertips in the form of an iPhone app. About the Author Dr. Jesús Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.