The Book Of Alternative Data

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The Book of Alternative Data

Author : Alexander Denev,Saeed Amen
Publisher : John Wiley & Sons
Page : 416 pages
File Size : 41,7 Mb
Release : 2020-07-21
Category : Business & Economics
ISBN : 9781119601791

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The Book of Alternative Data by Alexander Denev,Saeed Amen Pdf

The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.

The Book of Alternative Data

Author : Alexander Denev,Saeed Amen
Publisher : John Wiley & Sons
Page : 416 pages
File Size : 43,5 Mb
Release : 2020-07-02
Category : Business & Economics
ISBN : 9781119601814

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The Book of Alternative Data by Alexander Denev,Saeed Amen Pdf

The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.

Handbook of Alternative Data in Finance, Volume I

Author : Gautam Mitra,Christina Erlwein-Sayer,Kieu Thi Hoang,Diana Roman,Zryan Sadik
Publisher : CRC Press
Page : 478 pages
File Size : 50,6 Mb
Release : 2023-07-12
Category : Business & Economics
ISBN : 9781000897913

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Handbook of Alternative Data in Finance, Volume I by Gautam Mitra,Christina Erlwein-Sayer,Kieu Thi Hoang,Diana Roman,Zryan Sadik Pdf

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners

Handbook of Alternative Data in Finance, Volume I

Author : Gautam Mitra,Christina Erlwein-Sayer,Kieu Thi Hoang,Diana Roman,Zryan Sadik
Publisher : CRC Press
Page : 488 pages
File Size : 41,8 Mb
Release : 2023-07-12
Category : Business & Economics
ISBN : 9781000897982

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Handbook of Alternative Data in Finance, Volume I by Gautam Mitra,Christina Erlwein-Sayer,Kieu Thi Hoang,Diana Roman,Zryan Sadik Pdf

Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners

Handbook of Alternative Data in Finance

Author : Gautam Mitra,Christina Erlwein-Sayer,Kieu Thi Hoang,Diana Roman,Zryan Sadik
Publisher : C&h/CRC Press
Page : 0 pages
File Size : 46,6 Mb
Release : 2023
Category : Finance
ISBN : 1032276703

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Handbook of Alternative Data in Finance by Gautam Mitra,Christina Erlwein-Sayer,Kieu Thi Hoang,Diana Roman,Zryan Sadik Pdf

"Handbook of Alternative Data in Finance, Volume I Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners"--

The AI Book

Author : Ivana Bartoletti,Anne Leslie,Shân M. Millie
Publisher : John Wiley & Sons
Page : 782 pages
File Size : 48,7 Mb
Release : 2020-04-09
Category : Business & Economics
ISBN : 9781119551928

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The AI Book by Ivana Bartoletti,Anne Leslie,Shân M. Millie Pdf

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

The Only Guide to Alternative Investments You'll Ever Need

Author : Larry E. Swedroe,Jared Kizer
Publisher : John Wiley and Sons
Page : 238 pages
File Size : 43,7 Mb
Release : 2010-05-13
Category : Business & Economics
ISBN : 9780470885338

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The Only Guide to Alternative Investments You'll Ever Need by Larry E. Swedroe,Jared Kizer Pdf

The rewards of carefully chosen alternative investments can be great. But many investors don’t know enough about unfamiliar investments to make wise choices. For that reason, financial advisers Larry Swedroe and Jared Kizer designed this book to bring investors up to speed on the twenty most popular alternative investments: Real estate, Inflation-protected securities, Commodities, International equities, Fixed annuities, Stable-value funds, High-yield (junk) bonds, Private equity (venture capital), Covered calls, Socially responsible mutual funds, Precious metals equities, Preferred stocks, Convertible bonds, Emerging market bonds, Hedge funds, Leveraged buyouts, Variable annuities, Equity-indexed annuities, Structured investment products, Leveraged funds The authors describe how the investments work, the pros and cons of each, which to consider, which to avoid, and how to get started. Swedroe and Kizer evaluate each investment in terms of: Expected returns Volatility Distribution of returns Diversification potential Fees Trading and operating expenses Liquidity Tax efficiency Account location Role in an asset-allocation program Any investor who is considering or just curious about investment opportunities outside the traditional world of stocks, bonds, and bank certificates of deposit would be well-advised to read this book.

Big Data for Twenty-First-Century Economic Statistics

Author : Katharine G. Abraham,Ron S. Jarmin,Brian C. Moyer,Matthew D. Shapiro
Publisher : University of Chicago Press
Page : 502 pages
File Size : 40,9 Mb
Release : 2022-03-11
Category : Business & Economics
ISBN : 9780226801254

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Big Data for Twenty-First-Century Economic Statistics by Katharine G. Abraham,Ron S. Jarmin,Brian C. Moyer,Matthew D. Shapiro Pdf

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

Data-Driven Investing, + Website

Author : Matei Zatreanu
Publisher : Wiley
Page : 0 pages
File Size : 53,5 Mb
Release : 2025-04-29
Category : Business & Economics
ISBN : 1119429633

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Data-Driven Investing, + Website by Matei Zatreanu Pdf

Implement a data-driven investment strategy The investing landscape is increasingly driven by big data and artificial intelligence. For most finance professionals, big data, statistics, and programming are outside their comfort zone. Yet, proficiency in these areas is becoming a prerequisite for successful investing. And while there are plenty of resources on these individual topics, what is missing is a framework for combining these disciplines for investment purposes. Data-Driven Investing shows readers how investment decisions can be made or improved through the use of alternative datasets and inference techniques. The author covers artificial intelligence algorithms, data visualization, and data sourcing to show how these components come together to form a more robust investment strategy. The goal is to help finance professionals prepare for an investing landscape increasingly driven by big data and artificial intelligence. Shows how investing wisdom can be harnessed through science and augmented by data Demonstrates how an augmented investing philosophy promises a deeper understanding of future economic performance Is essential reading for fund managers, research analysts, quantitative investors, data scientists, and general finance professionals Includes a companion website with code, data sets, and videos providing more in-depth information on augmented/data-driven investing This book comes at a time of increasing investor anxiety with lackluster hedge fund performance, which is causing many funds to explore data-driven investing as a possible evolution of their strategies.

Handbook of Alternative Assets

Author : Mark J. P. Anson
Publisher : John Wiley & Sons
Page : 720 pages
File Size : 42,5 Mb
Release : 2008-04-15
Category : Business & Economics
ISBN : 0470089229

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Handbook of Alternative Assets by Mark J. P. Anson Pdf

Since the first edition of the Handbook of Alternative Assets was published, significant events-from the popping of the technology bubble and massive accounting scandals to recessions and bear markets-have shifted the financial landscape. These changes have provided author Mark J. P. Anson with an excellent opportunity to examine alternative assets during a different part of the economic cycle than previously observed in the first edition. Fully revised and updated to reflect today's financial realities, the Handbook of Alternative Assets, Second Edition covers the five major classes of alternative assets-hedge funds, commodity and managed futures, private equity, credit derivatives, and corporate governance-and outlines the strategies you can use to efficiently incorporate these assets into any portfolio. Throughout the book, new chapters have been added, different data sources accessed, and new conclusions reached. Designed as both an introduction to the world of alternative assets and as a reference for the active investor, the Handbook of Alternative Assets, Second Edition will help you match alternative assets with your various investment goals.

The Little Book of Alternative Investments

Author : Ben Stein,Phil DeMuth
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 40,9 Mb
Release : 2011-02-25
Category : Business & Economics
ISBN : 1118075269

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The Little Book of Alternative Investments by Ben Stein,Phil DeMuth Pdf

Praise For THE LITTLE BOOK OF ALTERNATIVE INVESTMENTS "Ben and Phil have done it again. Another lucid, insightful book, designed to enhance your wealth! In today's stock-addled cult of equities, there is a gaping hole in most investors' portfolios...the whole panoply of alternative investments that can simultaneously help us cut our risk, better hedge our inflation risk, and boost our return. This Little Book is filled with big ideas on how to make these markets and strategies a treasured part of our investing toolkit." —Robert Arnott, Chairman, Research Affiliates "I have been reading Ben Stein for thirty-five years and Phil DeMuth since he joined up with Ben ten years ago. They do solid work, and this latest is no exception." —Jim Rogers, author of A Gift to My Children "If anyone can make hedge funds sexy, Stein and DeMuth can, and they've done it with style in this engaging, instructive, and tasteful how-to guide for investing in alternatives. But you should read this Kama Sutra of investment manuals not just for the thrills, but also to learn how to avoid the hazards of promiscuous and unprotected investing." —Andrew Lo, Professor and Director, MIT Laboratory for Financial Engineering

Applied Missing Data Analysis

Author : Craig K. Enders
Publisher : Guilford Press
Page : 401 pages
File Size : 50,7 Mb
Release : 2010-04-23
Category : Psychology
ISBN : 9781606236390

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Applied Missing Data Analysis by Craig K. Enders Pdf

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists. This book will appeal to researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science. It will also serve as a supplemental text for doctoral-level courses or seminars in advanced quantitative methods, survey analysis, longitudinal data analysis, and multilevel modeling, and as a primary text for doctoral-level courses or seminars in missing data.

Big Data Science in Finance

Author : Irene Aldridge,Marco Avellaneda
Publisher : John Wiley & Sons
Page : 336 pages
File Size : 42,8 Mb
Release : 2021-01-08
Category : Computers
ISBN : 9781119602972

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Big Data Science in Finance by Irene Aldridge,Marco Avellaneda Pdf

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. 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 vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Machine Learning for Algorithmic Trading

Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Page : 822 pages
File Size : 46,9 Mb
Release : 2020-07-31
Category : Business & Economics
ISBN : 9781839216787

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Machine Learning for Algorithmic Trading by Stefan Jansen Pdf

Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.

R for Data Science

Author : Hadley Wickham,Garrett Grolemund
Publisher : "O'Reilly Media, Inc."
Page : 521 pages
File Size : 43,7 Mb
Release : 2016-12-12
Category : Computers
ISBN : 9781491910368

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R for Data Science by Hadley Wickham,Garrett Grolemund Pdf

Learn how to use R to turn raw data into insight, knowledge, and understanding. 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, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results