Topics covered include matrix multiplication, row reduction, matrix inverse, orthogonality and computation. The self-teaching book is loaded with examples and graphics and provides a wide array of probing problems, accompanying solutions, and a glossary. Chapter 1: Introduction to Vectors; Chapter 2: Solving Linear Equations; Chapter 3: Vector Spaces and Subspaces; Chapter 4: Orthogonality; Chapter 5: Determinants; Chapter 6: Eigenvalues and Eigenvectors; Chapter 7: Linear Transformations; Chapter 8: Applications; Chapter 9: Numerical Linear Algebra; Chapter 10: Complex Vectors and Matrices; Solutions to Selected Exercises; Final Exam. Matrix Factorizations. Conceptual Questions for Review. Glossary: A Dictionary for Linear Algebra Index Teaching Codes Linear Algebra in a Nutshell.

    Ernest Chan, a respected independent trader and consultant, will show you how. Whether you're an independent retail trader looking to start your own quantitative trading business or an individual who aspires to work as a quantitative trader at a major financial institution, this practical guide contains the information you need to succeed.

    There can be so much information available that you can't even decide where to start. Or worse, you start down the path of learning and quickly discover too many concepts, commands, and nuances that aren't explained. This kind of experience is frustrating and leaves you with more questions than answers.Python Programming for Beginners doesn't make any assumptions about your background or knowledge of Python or computer programming. You need no prior knowledge to benefit from this book. You will be guided step by step using a logical and systematic approach. As new concepts, commands, or jargon are encountered they are explained in plain language, making it easy for anyone to understand. Here is what you will learn by reading Python Programming for Beginners: When to use Python 2 and when to use Python 3. How to install Python on Windows, Mac, and Linux. Screenshots included. How to prepare your computer for programming in Python. The various ways to run a Python program on Windows, Mac, and Linux. Suggested text editors and integrated development environments to use when coding in Python. How to work with various data types including strings, lists, tuples, dictionaries, booleans, and more. What variables are and when to use them. How to perform mathematical operations using Python. How to capture input from a user. Ways to control the flow of your programs. The importance of white space in Python. How to organize your Python programs -- Learn what goes where. What modules are, when you should use them, and how to create your own. How to define and use functions. Important built-in Python functions that you'll use often. How to read from and write to files. The difference between binary and text files. Various ways of getting help and find Python documentation. Much more... Every single code example in the book is available to download, providing you with all the Python code you need at your fingertips! Scroll up, click the Buy Now With 1 Click button and get started learning Python today!

    An authoritative introduction to "fuzzy logic" brings readers up to speed on the "smart" products and computers that will change all of our lives in the future.

    

    Words are the most powerful things in the universe today. They can defeat you or they can bring you life. They can make the difference in your finances and your well-being. God created the universe by speaking it into existence and He has given you that same ability. Learn to turn your financial situation around by following the powerful principles of faith contained in this book. Don’t live another day in lack – start releasing the ability of God through faith-filled words!

    One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

    Now a #1 Amazon Best Seller, this step-by-step guide by expert Sarah McHarry will walk you through the essential first steps to creating your own website or blog. In the book's Quick Start Guide, Sarah shows you how to make a website with WordPress in eight easy lessons. In the In-Depth Guide, Sarah introduces you to some of the more advanced techniques to help you develop your WordPress website into a fully functional, professional web presence. What you'll learn in this book:How to get your domain and the right WordPress hostingHow to install WordPress with a few clicks of the mouseHow to design a professional-looking WordPress websiteAdding posts and pagesHow to use graphics and imagesAll about themes, plugins and widgets... and lots more...Important: this guide is up-to-date for the current release of WordPress 3.3.1!Whether you want a simple WordPress blog or a full-blown ecommerce site, Sarah's 'WordPress To Go' will start you off on the right foot.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    Weygandt, Paul D. Kimmel, and Donald E. Kieso, which incorporates International Financial Reporting Standards (IFRS) into the existing textbook framework. On almost every page, the book addresses every accounting topic from the perspective of IFRS while still highlighting key differences between IFRS and US GAAP. Following the reputation for accuracy, comprehensiveness, and currency, the authors have painstakingly created a book dedicated to assisting students learning accounting topics under the rules of IFRS.

    

    Absolutely:•No Trendlines•No Support or Resistance analysis•No ADX•No RSI•No Fibonacci Retracements of Extensions of any kind•No Elliot wave•No Candlestick patterns ( triangles, rectangles, pendants, Flags,…..)•No Bollinger Bands•No StochasticWelcome to the world of Pure Price action at its finest.PRICE ACTION the like of which you have never seen before. Identify current Trend at a Glance; quickly assess whether you are at the beginning of the move or whether you are late.All you need is a FREE Metatrader 4 platform and this Book.

    Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.