Download Full eBooks in PDF
The Little Shepherd Of Kingdom Come Volume 2 Of 2 Easyread Super Large 24pt Edition Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of The Little Shepherd Of Kingdom Come Volume 2 Of 2 Easyread Super Large 24pt Edition book. This book definitely worth reading, it is an incredibly well-written.
Author : Anonim
Publisher : ReadHowYouWant.com
Page : 426 pages
File Size : 41,9 Mb
Release : 2000
Category : Electronic
ISBN : 9781427074584
Author : Anonim
Publisher : ReadHowYouWant.com
Page : 430 pages
File Size : 47,8 Mb
Release : 2000
Category : Electronic
ISBN : 9781427074416
Author : Damian Sharp
Publisher : Conari Press
Page : 325 pages
File Size : 43,8 Mb
Release : 2007-01-01
Category : Body, Mind & Spirit
ISBN : 9781609251147
A basic introduction to the ancient system of astrology based on the Chinese lunar calendar from the author of Simple Feng Shui. Introduced by the emperor Huang Ti between 2700 and 2600 B.C.E., Chinese astrology is based on the culture’s lunar calendar, which is made up of five cycles of twelve years each, with a complete cycle taking sixty years. According to legend, Buddha summoned all the animals to come to him before he departed earth, but only twelve came to pay their respects. To honor them, he named a year after each animal in the order that they appeared: Rat, Ox, Tiger, Rabbit, Dragon, Snake, Horse, Sheep, Monkey, Rooster, Dog, and Boar. These became the twelve astrological signs that determine your personality, behavior, and proclivities according to the year and time of day you were born. This age-old practice tells you what to expect—in life, career, and romance—in the coming years. Featuring illustrations and tables, this guide makes this exacting science and art of divination and personal analysis accessible to Western readers.
Author : Edward H. Thompson
Publisher : SAGE Publications
Page : 289 pages
File Size : 42,6 Mb
Release : 1994-06-07
Category : Social Science
ISBN : 9781452255026
The first comprehensive exploration on the subject of older men, Older Men′s Lives offers a multidisciplinary portrait of men and their concerns in later life. Using both a life-course and gendered perspective, the contributors to this collection of original articles point out that the image and self-image of men are continuously reconstructed over the life cycle. They examine older men′s position in society and the changes wrought in their status and roles over time. Their relationship with their spouses, children, grandchildren, and friends are also explored, as are policy implications of a gendered, life-cycle view of masculinity. This volume also discusses faith development in older men, masculinity identity from work to retirement, older men′s sexuality, and older men′s friendship patterns. Older Men′s Lives will be of interest to professionals and students interested in gender, men′s studies, gerontology, and sociology. "This book begins to remedy the lack of information and provides data and research on aging men. . . .The strength of this book is the specificity of its focus. By focusing solely on male concerns the book is able to identify issues in the male aging process and discuss them on their own terms rather than simply as a contrast to females." --Clinical Gerontologist
Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
Page : 750 pages
File Size : 45,6 Mb
Release : 2014-12-11
Category : Computers
ISBN : 9781491945384
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
Author : Eryk Lewinson
Publisher : Packt Publishing Ltd
Page : 426 pages
File Size : 40,8 Mb
Release : 2020-01-31
Category : Computers
ISBN : 9781789617320
Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook Description Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach. What you will learnDownload and preprocess financial data from different sourcesBacktest the performance of automatic trading strategies in a real-world settingEstimate financial econometrics models in Python and interpret their resultsUse Monte Carlo simulations for a variety of tasks such as derivatives valuation and risk assessmentImprove the performance of financial models with the latest Python librariesApply machine learning and deep learning techniques to solve different financial problemsUnderstand the different approaches used to model financial time series dataWho this book is for This book is for financial analysts, data analysts, and Python developers who want to learn how to implement a broad range of tasks in the finance domain. Data scientists looking to devise intelligent financial strategies to perform efficient financial analysis will also find this book useful. Working knowledge of the Python programming language is mandatory to grasp the concepts covered in the book effectively.
Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
Page : 478 pages
File Size : 42,9 Mb
Release : 2020-10-14
Category : Business & Economics
ISBN : 9781492055389
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
Author : James Ma Weiming
Publisher : Packt Publishing Ltd
Page : 340 pages
File Size : 45,5 Mb
Release : 2015-04-29
Category : Computers
ISBN : 9781784397876
If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.
Author : Yuxing Yan
Publisher : Packt Publishing Ltd
Page : 653 pages
File Size : 52,9 Mb
Release : 2014-04-25
Category : Computers
ISBN : 9781783284382
A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.
Author : Krish Naik
Publisher : Unknown
Page : 378 pages
File Size : 51,7 Mb
Release : 2019-03-29
Category : Computers
ISBN : 1789346371
Learn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras Key Features Understand Python data structure fundamentals and work with time series data Use popular Python libraries including TensorFlow, Keras, and SciPy to deploy key concepts in quantitative finance Explore various Python programs and learn finance paradigms Book Description Python is one of the most popular languages used for quantitative finance. With this book, you'll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management. The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you'll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and optimize your portfolio by implementing Markowitz Portfolio Optimization. Sections on regression analysis methodology will help you to value assets and understand the relationship between commodity prices and business stocks. In addition to this, you'll be able to forecast stock prices using Monte Carlo simulation. The book will also highlight forecast models that will show you how to determine the price of a call option by analyzing price variation. You'll also use deep learning for financial data analysis and forecasting. In the concluding chapters, you will create neural networks with TensorFlow and Keras for forecasting and prediction. By the end of this book, you will be equipped with the skills you need to perform different financial analysis tasks using Python What you will learn Clean financial data with data preprocessing Visualize financial data using histograms, color plots, and graphs Perform time series analysis with pandas for forecasting Estimate covariance and the correlation between securities and stocks Optimize your portfolio to understand risks when there is a possibility of higher returns Calculate expected returns of a stock to measure the performance of a portfolio manager Create a prediction model using recurrent neural networks (RNN) with Keras and TensorFlow Who this book is for This book is ideal for aspiring data scientists, Python developers and anyone who wants to start performing quantitative finance using Python. You can also make this beginner-level guide your first choice if you're looking to pursue a career as a financial analyst or a data analyst. Working knowledge of Python programming language is necessary.
Author : Thomas Hardy,Peter Washington
Publisher : Everyman Chess
Page : 254 pages
File Size : 52,5 Mb
Release : 1995
Category : Electronic
ISBN : 1857157176
Distringuished as both a great novelist and a great poet. Thomas Hardy (1840-1928) had a writing career which spanned more than sixty years, concentrating first on prose and then, after publishing his last novel in 1895, on verse. A master of the short lyric and the vivid narrative, Hardy is pre-eminently the poet of remembrance and tender regret for lost happiness; but he is also an ironist whose exquisite descriptions of rural life are the setting for bitingly sharp observations of human frailty.
Author : Ho, Peter Kwok Man
Publisher : Scarborough, Ont. : Prentice-Hall Canada
Page : 45 pages
File Size : 40,8 Mb
Release : 1994-01-01
Category : Astrology, Chinese
ISBN : 013305442X
Author : James Ma Weiming
Publisher : Packt Publishing Ltd
Page : 414 pages
File Size : 52,5 Mb
Release : 2019-04-30
Category : Computers
ISBN : 9781789345278
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key FeaturesExplore advanced financial models used by the industry and ways of solving them using PythonBuild state-of-the-art infrastructure for modeling, visualization, trading, and moreEmpower your financial applications by applying machine learning and deep learningBook Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learnSolve linear and nonlinear models representing various financial problemsPerform principal component analysis on the DOW index and its componentsAnalyze, predict, and forecast stationary and non-stationary time series processesCreate an event-driven backtesting tool and measure your strategiesBuild a high-frequency algorithmic trading platform with PythonReplicate the CBOT VIX index with SPX options for studying VIX-based strategiesPerform regression-based and classification-based machine learning tasks for predictionUse TensorFlow and Keras in deep learning neural network architectureWho this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.
Author : Kim Zetter
Publisher : Conari Press
Page : 232 pages
File Size : 42,5 Mb
Release : 2004-03-01
Category : Body, Mind & Spirit
ISBN : 9781609252052
In Simple Kabbalah, journalist and Jewish scholar Kim Zetter outlines the history of this mystic tradition, the main tenets of its belief system, and explains its central symbol, the Tree of Life. She then shows how to practice the wisdom of Kabbalah in everyday life through meditation and exercises for calming the mind and sharpening awareness. As we gradually absorb this ancient form of knowledge, we see how it affects every aspect of our lives, from attitudes about work and the environment to our social and personal interactions. Despite its popularity at cocktail parties and in the media, few people genuinely understand what Kabbalah is. Unlike traditional Judaism, Kabbalah views God as a divine source of light, energy, and love, ever present in the physical world, rather than a patriarchal diety. Kabbalah practitioners look beyond a literal interpretation of the Hebrew Bible for information about the soul; the nature of God, Creation, and the spiritual world; and humans' relationship to God and to each other.
Author : Thomas Hardy
Publisher : Unknown
Page : 274 pages
File Size : 46,8 Mb
Release : 1884
Category : Electronic
ISBN : BSB:BSB11664339