Found inside – Page 38Proceedings of the 2nd International Data Science Conference – iDSC2019 Peter Haber, Thomas Lampoltshammer, Manfred Mayr. (b) Fig. 1: Topic classification ... A comprehensive introduction to statistics that teaches the fundamentals with real-life scenarios, and covers histograms, quartiles, probability, Bayes' theorem, predictions, approximations, random samples, and related topics. Found inside – Page 317We present some significant topics inferred through LDA using wordcloud in ... a topic: The wordclouds show some related, interesting words to name topics ... Found inside – Page xviIn the current era of data science, we have many rich and interesting data sets to use for ... We chose problems that address various topics, technologies, ... Found insideThe text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. And it’s all there for your company to strategically utilize for giant profits! But where to begin?Think Bigger provides a roadmap for organizations looking to develop a profitable big data strategy. Found insideAbout the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. Found inside – Page iThis book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers ... Found inside – Page 2392 Workflow of Big data, representing the various stages through which data are ... Big data analytics is becoming the one of the most interesting topics ... "This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"-- Found insideIn this book, you'll cover different ways of downloading financial data and preparing it for modeling. Found insideThe book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential. Let this book be your guide. Data Science For Dummies is for working professionals and students interested in transforming an organization's sea of structured, semi-structured, and unstructured data into actionable business insights. Found insideDatascience is abroad field that intersects with many other fields,such as ... As a result,this booktouches onmany interesting topics that unfortunately ... Found inside – Page 102... volume and variety of available data makes it easy to find intrinsically interesting research topics in applied statistics. Furthermore, data science is ... Found insideThe volume is suitable for researchers in data science in industry and academia. This edited volume on data science features a variety of research ranging from theoretical to applied and computational topics. Found insideThis book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. Found insideI also consumed interesting writings about algorithms, data science, innovation, innovative techniques, brain chemistry, bias, and other topics related to ... But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. Found inside – Page 48Many forum search facilities are able to help in finding threads with interesting topics. Although the main post (inquiry) is clearly represented in the ... Found insideStyle and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. The Data Science Handbook is a curated collection of 25 candid, honest and insightful interviews conducted with some of the world's top data scientists.In this book, you'll hear how the co-creator of the term 'data scientist' thinks about ... Found inside“Highest Prob” terms are the same ones we used in the previous plot, the most common ones in the topic. Another interesting measure is “FREX”, ... Found inside – Page 75The following list outlines future interesting topics for research and new avenues proposed for dealing with these challenges: 1. Found insideA Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. Found inside – Page 395The two posts appear at http://conductrics.com/ data‐science‐resources/ and ... provides you with an amazing array of essays on various data science topics. The volume is suitable for researchers in data science in industry and academia. This edited volume on data science features a variety of research ranging from theoretical to applied and computational topics. Past, Present, and Future of Statistical Science was commissioned in 2013 by the Committee of Presidents of Statistical Societies (COPSS) to celebrate its 50th anniversary and the International Year of Statistics. Found inside – Page 39With the STM analytics agent on-premise analysis reduces data traffic, ... various data analytics algorithms are interesting topics for continuing research. Found inside"author" : "Joel Grus", "publicationYear" : 2014, "topics" : [ "data", "science", "data science"] } We can parse JSON using Python's json module. Presents case studies and instructions on how to solve data analysis problems using Python. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. Found insideIn this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses. Found insideFinally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. Found inside – Page 233We can see that the pins are centered on topics such as machine learning, data science, data analysis, or big data. The interesting aspect of the preceding ... This guide also helps you understand the many data-mining techniques in use today. Found inside – Page 274Topic. Models,. Nonnegative. Matrix. Factorization, ... An interesting point to note here is that these algorithms did not aim to explicitly learn a model ... Found inside – Page 10Big data means big research. Without strong collaborative efforts between the experts from many disciplines (e.g., mathematics, statistics, computer science ... 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 ... This book presents some of the most important modeling and prediction techniques, along with relevant applications. Found insideWhat you will learn Learn data wrangling with Python and Pandas for your data science and AI projects Automate tasks such as text classification, email filtering, and web scraping with Python Use Matplotlib to generate a variety of stunning ... This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three sections: The first section is an introduction to data science. Found inside – Page 22To understand some of the deeper concepts, such as data mining, natural language ... Big Data, analytics and other very interesting and challenging topics. Found inside – Page 46Normalized closeness centrality of 30 topics In the most recent 5-year interval computer vision and data analytics are high centrality topics. Found insideThe book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. Found inside – Page 138Building Data Analytics Applications with Hadoop Russell Jurney. {% for item in topics['topics'] -%}