Mastering Data Science And Big Data Analytics

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Mastering Data Science And Big Data Analytics

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Author : Maxine Chen
language : en
Publisher:
Release Date : 2024-03-02

Mastering Data Science And Big Data Analytics written by Maxine Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-02 with Computers categories.

Embark on a transformative journey into the realm of data science and big data analytics with 'Mastering Data Science and Big Data Analytics: Strategies and Tools for Effective Analysis.' This comprehensive guide unveils essential techniques, strategies, and tools necessary to navigate the vast landscape of big data with confidence and proficiency. From foundational concepts to advanced methodologies, this book provides a holistic understanding of data science principles, empowering both aspiring data scientists and seasoned professionals alike to harness the power of data to drive informed decision-making and innovation. Through clear explanations and real-world examples, discover how to leverage cutting-edge tools and technologies to extract actionable insights from complex datasets. With a focus on practical application, 'Mastering Data Science and Big Data Analytics' equips you with the skills to tackle real-world challenges head-on, whether it's uncovering hidden patterns, predicting future trends, or optimizing business processes. Explore the latest advancements in machine learning, artificial intelligence, and data visualization, and gain proficiency in popular programming languages and frameworks such as Python, R, TensorFlow, and Apache Spark. Whether you're a data enthusiast looking to expand your skill set or a business leader striving to unlock the full potential of your data assets, this book serves as an indispensable companion on the journey to mastering data science and big data analytics. Empower yourself to turn data into actionable insights and drive meaningful impact in an increasingly data-driven world.

Mastering Data Science And Big Data Analytics

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Author : Nikhilesh Mishra
language : en
Publisher: Independently Published
Release Date : 2023-08-25

Mastering Data Science And Big Data Analytics written by Nikhilesh Mishra and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-25 with categories.

Embark on an illuminating voyage through the captivating landscape of "Mastering Data Science and Big Data Analytics: Concepts, Techniques, and Application" From foundational principles to advanced methodologies, this comprehensive guide empowers you with the wisdom and expertise to navigate the intricate world of data science and big data analytics. Explore the fundamental concepts of data science, from data acquisition to predictive modeling. Dive deep into cutting-edge techniques, including exploratory data analysis and machine learning. Gain practical insights from real-world data analysis projects spanning diverse industries. Uncover the ethical considerations and societal implications of data-driven decision-making. Enhance your growth potential with an exclusive section dedicated to interviews and interviewers, providing valuable insights and skills that amplify your journey towards success. Whether you're a budding enthusiast or a seasoned practitioner, "Mastering Data Science and Big Data Analytics: Concepts, Techniques, and Applications" empowers you to elevate your expertise and become a visionary in the realm of data-driven innovation. Seize the opportunity-secure your copy today and embark on a transformative journey of knowledge and exploration!

Mastering Python For Data Science

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Author : Samir Madhavan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-08-31

Mastering Python For Data Science written by Samir Madhavan 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 2015-08-31 with Computers categories.

Explore the world of data science through Python and learn how to make sense of data About This Book Master data science methods using Python and its libraries Create data visualizations and mine for patterns Advanced techniques for the four fundamentals of Data Science with Python - data mining, data analysis, data visualization, and machine learning Who This Book Is For If you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed. What You Will Learn Manage data and perform linear algebra in Python Derive inferences from the analysis by performing inferential statistics Solve data science problems in Python Create high-end visualizations using Python Evaluate and apply the linear regression technique to estimate the relationships among variables. Build recommendation engines with the various collaborative filtering algorithms Apply the ensemble methods to improve your predictions Work with big data technologies to handle data at scale In Detail Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving. This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science. Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods. Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics. Style and approach This book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios.

Creating Value With Data Analytics In Marketing

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Author : Peter C. Verhoef
language : en
Publisher: Routledge
Release Date : 2021-11-07

Creating Value With Data Analytics In Marketing written by Peter C. Verhoef and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-07 with Business & Economics categories.

This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science. The vast amount of data generated about us and our world is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organizations to leverage the information to create value in marketing. Creating Value with Data Analytics in Marketing provides a nuanced view of big data developments and data science, arguing that big data is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. The second edition of this bestselling text has been fully updated in line with developments in the field and includes a selection of new, international cases and examples, exercises, techniques and methodologies. Tying data and analytics to specific goals and processes for implementation makes this essential reading for advanced undergraduate and postgraduate students and specialists of data analytics, marketing research, marketing management and customer relationship management. Online resources include chapter-by-chapter lecture slides and data sets and corresponding R code for selected chapters.

Mastering Spark For Data Science

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Author : Andrew Morgan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-29

Mastering Spark For Data Science written by Andrew Morgan 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 2017-03-29 with Computers categories.

Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products About This Book Develop and apply advanced analytical techniques with Spark Learn how to tell a compelling story with data science using Spark's ecosystem Explore data at scale and work with cutting edge data science methods Who This Book Is For This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes. What You Will Learn Learn the design patterns that integrate Spark into industrialized data science pipelines See how commercial data scientists design scalable code and reusable code for data science services Explore cutting edge data science methods so that you can study trends and causality Discover advanced programming techniques using RDD and the DataFrame and Dataset APIs Find out how Spark can be used as a universal ingestion engine tool and as a web scraper Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams Study advanced Spark concepts, solution design patterns, and integration architectures Demonstrate powerful data science pipelines In Detail Data science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs. This book deep dives into using Spark to deliver production-grade data science solutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more. You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly. Style and approach This is an advanced guide for those with beginner-level familiarity with the Spark architecture and working with Data Science applications. Mastering Spark for Data Science is a practical tutorial that uses core Spark APIs and takes a deep dive into advanced libraries including: Spark SQL, visual streaming, and MLlib. This book expands on titles like: Machine Learning with Spark and Learning Spark. It is the next learning curve for those comfortable with Spark and looking to improve their skills.

Data Science

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Author : Herbert Jones
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-11

Data Science written by Herbert Jones and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11 with categories.

Did you know that the value of data usage has increased job opportunities, but that there are few specialists? These days, everyone is aware of the role that data can play, whether it is an election, business or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype? This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't, presents you with a step-by-step approach to Data Science as well as secrets only known by the best Data Scientists. It combines analytical engineering, Machine Learning, Big Data, Data Mining, and Statistics in an easy to read and digest method. Data gathered from scientific measurements, customers, IoT sensors, and so on is very important only when one can draw meaning from it. Data Scientists are professionals that help disclose interesting and rewarding challenges of exploring, observing, analyzing, and interpreting data. To do that, they apply special techniques that help them discover the meaning of data. Becoming the best Data Scientist is more than just mastering analytic tools and techniques. The real deal lies in the way you apply your creative ability like expert Data Scientists. This book will help you discover that and get you there. The goal with Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't is to help you expand your skills from being a basic Data Scientist to becoming an expert Data Scientist ready to solve real-world data centric issues. At the end of this book, you will learn how to combine Machine Learning, Data Mining, analytics, and programming, and extract real knowledge from data. As you read, you will discover important statistical techniques and algorithms that are helpful in learning Data Science. When you have finished, you will have a strong foundation to help you explore many other fields related to Data Science. This book will discuss the following topics: What Data Science is What it takes to become an expert in Data Science Best Data Mining techniques to apply in data Data visualization Logistic regression Data engineering Machine Learning Big Data Analytics And much more! Don't waste any time. Grab your copy today and learn quick tips from the best Data scientists!

Data Analytics

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Author : Robert Keane
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-09-24

Data Analytics written by Robert Keane and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-24 with Big data categories.

Data Analytics Master The Techniques For Data Science, Big Data And Data Analytics If your business is like most, it is already generating a staggering amount of data on a regular basis. Understanding what this data truly means is key to succeeding in the marketplace these days and if you are looking for a way to give yourself an edge then Data Analytics is the book you have been waiting for. Inside you will find the tools you need in order to take full advantage of all of the data that your business is already generating regardless if you are part of a major corporation or if you are a small business that is just starting out. There are currently over a quintillion byte of data being created each and every day and if you aren't considering how you can make the most of your share then you are already losing out to the competition. Inside this book you will find: Everything you need to know to get started completing the right kind of data analysis to benefit your business regardless of what that business is. The best ways to utilize predictive analysis effectively. Easy to use machine learning and regression techniques. The reasons why you need discrete choice models in your life. And more... So, what are you waiting for? Don't get left behind, do your business a favor and buy this book today! Scroll Up And Click The "BUY" Button!

Statistics For Data Science

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Author : James D. Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-17

Statistics For Data Science written by James D. Miller 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 2017-11-17 with Computers categories.

Get your statistics basics right before diving into the world of data science About This Book No need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs; Implement statistics in data science tasks such as data cleaning, mining, and analysis Learn all about probability, statistics, numerical computations, and more with the help of R programs Who This Book Is For This book is intended for those developers who are willing to enter the field of data science and are looking for concise information of statistics with the help of insightful programs and simple explanation. Some basic hands on R will be useful. What You Will Learn Analyze the transition from a data developer to a data scientist mindset Get acquainted with the R programs and the logic used for statistical computations Understand mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more Learn to implement statistics in data science tasks such as data cleaning, mining, and analysis Learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks Get comfortable with performing various statistical computations for data science programmatically In Detail Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on. This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks. By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically. Style and approach Step by step comprehensive guide with real world examples

Mastering Data Science

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Author : Cybellium Ltd
language : en
Publisher: Cybellium Ltd
Release Date :

Mastering Data Science written by Cybellium Ltd and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

Unleash the Power of Insights from Data Are you ready to embark on a transformative journey into the world of data science? "Mastering Data Science" is your comprehensive guide to unlocking the full potential of data for extracting valuable insights and driving informed decisions. Whether you're an aspiring data scientist looking to enhance your skills or a business leader seeking to leverage data-driven strategies, this book equips you with the knowledge and tools to master the art of data science. Key Features: 1. Dive into Data Science: Immerse yourself in the realm of data science, understanding its core principles, methodologies, and applications. Build a solid foundation that empowers you to extract meaningful insights from complex datasets. 2. Data Exploration and Visualization: Master the art of data exploration and visualization. Learn how to analyze datasets, uncover patterns, and create compelling visualizations that reveal hidden trends. 3. Statistical Analysis and Hypothesis Testing: Uncover the power of statistical analysis and hypothesis testing. Explore techniques for making data-driven inferences, validating assumptions, and drawing meaningful conclusions. 4. Machine Learning Fundamentals: Delve into machine learning concepts and techniques. Learn about supervised and unsupervised learning, feature engineering, model selection, and evaluation. 5. Predictive Analytics: Discover the realm of predictive analytics. Learn how to build predictive models that forecast future outcomes, enabling proactive decision-making. 6. Natural Language Processing (NLP) and Text Mining: Explore NLP and text mining techniques. Learn how to process and analyze textual data, extract sentiments, and uncover insights from unstructured content. 7. Time Series Analysis: Master time series analysis for modeling sequential data. Learn how to forecast trends, identify seasonality, and make predictions based on temporal patterns. 8. Big Data and Data Wrangling: Dive into big data analytics and data wrangling. Learn how to handle and preprocess large datasets, ensuring data quality and usability. 9. Deep Learning and Neural Networks: Uncover the world of deep learning and neural networks. Learn how to build and train deep learning models for tasks like image recognition and natural language understanding. 10. Real-World Applications: Gain insights into real-world applications of data science across industries. From healthcare to finance, explore how organizations harness data science for strategic decision-making. Who This Book Is For: "Mastering Data Science" is an indispensable resource for aspiring data scientists, analysts, and business professionals who want to excel in extracting insights from data. Whether you're new to data science or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of data for innovation. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Mastering Data Science With Python

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Author : Daniel Huston
language : en
Publisher:
Release Date : 2023-04-06

Mastering Data Science With Python written by Daniel Huston and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-06 with categories.