The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    The authors have eliminated unnecessary mathematical detail and concentrate on the intuition and insights that will be useful to practitioners throughout their careers as new ideas and challenges emerge from the financial marketplace. Essentials maintains the theme of asset allocation (authors discuss asset pricing and trading then apply these theories to portfolio planning in real-world securities markets that are governed by risk/return relationships).

    Whether you're a beginner, and avid student, or an armchair expert, you'll find plenty to stimulate you within this book.--book jacket

    Introduction; Financial Institutions, Financial Intermediaries, and Asset Management Firms; Depository Institutions: Activities and Characteristics; The U.S. Federal Reserve and the Creation of Money; Monetary Policy in the United States; Insurance Companies; Investment Companies and Exchange-Traded Funds; Pension Funds; Properties and Pricing of Financial Assets; The Level and Structure of Interest Rates; The Term Structure of Interest Rates; Risk/Return and Asset Pricing Models; Primary Markets and the Underwriting of Securities; Secondary Markets; Treasury and Agency Securities Markets; Municipal Securities Markets; Markets for Common Stock: The Basic Characteristics; Markets for Common Stock: Structure and Organization; Markets for Corporate Senior Instruments: I; Markets for Corporate Senior Instruments: II; The Markets for Bank Obligations; The Residential Mortgage Market; Residential Mortgage-Backed Securities Market; Market for Commercial Mortgage Loans and Commercial Mortgage-Backed Securities; Market for Asset-Backed Securities; Financial Futures Markets; Options Markets; Pricing of Futures and Options Contracts; The Applications of Futures and Options Contracts; OTC Interest Rate Derivatives: Forward Rate Agreements, Swaps, Caps, and Floors; Market for Credit Risk Transfer Vehicles: Credit Derivatives and Collateralized Debt Obligations; The Market for Foreign Exchange and Risk Control Instruments MARKET "Foundations of Financial Markets and Institutions," offers a comprehensive exploration of the revolutionary developments occurring in the world's financial markets and institutions i.e., innovation, globalization, and deregulation with a focus on the actual practices of financial institutions, investors, and financial instruments."

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    In his most important work, The General Theory of Employment, Interest, and Money (1936), Keynes critiqued the laissez-faire policies of his day, particularly the proposition that a normally functioning market economy would bring full employment. Keynes's forward-looking work transformed economics from merely a descriptive and analytic discipline into one that is policy oriented. For Keynes, enlightened government intervention in a nation's economic life was essential to curbing what he saw as the inherent inequalities and instabilities of unregulated capitalism.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    Sowell reveals the general principles behind any kind of economy-capitalist, socialist, feudal, and so on. In readable language, he shows how to critique economic policies in terms of the incentives they create, rather than the goals they proclaim. With clear explanations of the entire field, from rent control and the rise and fall of businesses to the international balance of payments, this is the first book for anyone who wishes to understand how the economy functions.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    This text uses a unified approach based on a single economics model that provides readers with a clear understanding of macroeconomics and its classical and Keynesian assumptions. Introduction: Introduction to Macroeconomics; The Measurement and Structure of the National Economy. Long-Run Economic Performance: Productivity, Output, and Employment; Consumption, Saving, and Investment; Saving and Investment in the Open Economy; Long-Run Economic Growth; The Asset Market, Money, and Prices. Business Cycles and Macroeconomic Policy: Business Cycles; The IS-LM/AD-AS Model: A General Framework for Macroeconomic Analysis; Classical Business Cycle Analysis: Market-Clearing Macroeconomics; Keynesianism: The Macroeconomics of Wage and Price Rigidity. Macroeconomic Policy: Its Environment and Institutions: Unemployment and Inflation; Exchange Rates, Business Cycles, and Macroeconomic Policy in the Open Economy; Monetary Policy and the Federal Reserve System; Government Spending and Its Financing. For all readers interested in intermediate macroeconomics.

    Features chapters on finance, marketing, accounting, strategy, quantitative analysis, operations, economics, organisational behaviour, and ethics, all revised to reflect the contemporary corporate culture and economic climate.

    Valuation provides up-to-date insights and practical advice on how to create, manage, and measure an organization's value. Along with all-new case studies that illustrate how valuation techniques and principles are applied in real-world situations, this comprehensive guide has been updated to reflect the events of the Internet bubble and its effect on stock markets, new developments in academic finance, changes in accounting rules (both U. S. and IFRS), and an enhanced global perspective. This edition contains the solid framework that managers at all levels, investors, and students have come to trust.

    In The Curse of Cash, Kenneth Rogoff, one of the world's leading economists, makes a persuasive and fascinating case for an idea that until recently would have seemed outlandish: getting rid of most paper money.Even as people in advanced economies are using less paper money, there is more cash in circulation--a record $1.4 trillion in U.S. dollars alone, or $4,200 for every American, mostly in $100 bills. And the United States is hardly exceptional. So what is all that cash being used for? The answer is simple: a large part is feeding tax evasion, corruption, terrorism, the drug trade, human trafficking, and the rest of a massive global underground economy.As Rogoff shows, paper money can also cripple monetary policy. In the aftermath of the recent financial crisis, central banks have been unable to stimulate growth and inflation by cutting interest rates significantly below zero for fear that it would drive investors to abandon treasury bills and stockpile cash. This constraint has paralyzed monetary policy in virtually every advanced economy, and is likely to be a recurring problem in the future.The Curse of Cash offers a plan for phasing out most paper money--while leaving small-denomination bills and coins in circulation indefinitely--and addresses the issues the transition will pose, ranging from fears about privacy and price stability to the need to provide subsidized debit cards for the poor.While phasing out the bulk of paper money will hardly solve the world's problems, it would be a significant step toward addressing a surprising number of very big ones. Provocative, engaging, and backed by compelling original arguments and evidence, The Curse of Cash is certain to spark widespread debate.