If you are struggling financially, you'll learn how to develop skills not taught in schools that will increase your income and Financial Confidence. If you are building or leading an organization, you'll get an inside look at how Dan Lok strategically scaled his organization through a combination of digital media and Social Capital, High-Ticket Closers, and an unbeatable team culture. Wherever you are, Unlock It will show you how to find your own way to achieving wealth, success, and significance.

    

    Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business dataUpdates that incorporate input from readers, changes in the field, and more material on statistics and machine learningDozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projectsComplete classroom support for instructors at www.mkp.com/datamining2e companion site

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

    It's not just a technical book or just a businessguide. Data is ubiquitous and it doesn't pay much attention toborders, so we've calibrated our coverage to follow it wherever itgoes.In the first edition of Big Data Now, the O'Reilly team tracked thebirth and early development of data tools and data science. Now, withthis second edition, we're seeing what happens when big data grows up:how it's being applied, where it's playing a role, and theconsequences -- good and bad alike -- of data's ascendance.We've organized the second edition of Big Data Now into five areas:Getting Up to Speed With Big Data -- Essential information on thestructures and definitions of big data.Big Data Tools, Techniques, and Strategies -- Expert guidance forturning big data theories into big data products.The Application of Big Data -- Examples of big data in action,including a look at the downside of data.What to Watch for in Big Data -- Thoughts on how big data will evolveand the role it will play across industries and domains.Big Data and Health Care -- A special section exploring thepossibilities that arise when data and health care come together.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    After getting caught reenacting what she sees, she runs away from home and seeks refuge in the streets of East Hammond,IN where she becomes vividly exposed to the rugged street life. Cuz: A focused hustler who's recently released from serving a 5 year sentence. Cuz places Precious under his wings, but only if she agrees to earn her keep by any means necessary. On their rise to power they encounter Shree, LaToya, Sonya, and Neicey. All five women have the same agenda needed for their journey at hand and agrees to live by Cuz's creed. "Never bite the hand that feeds you, unless that hand tries to slap the taste out of your mouth." Shaunta'e Howard is a new author to the game of books. Although she has been writing all her life this is her first release. She is a very outgoing young woman from Hammond, IN via Chicago, IL. She has a bachelor's degree in accounting from Devry University and a MBA in business from Keller Graduate School of Management. She is a mother of a 15 year old son and 5 year old daughter. In her spare time she enjoys reading, dancing, and any activity involving family and friends. Look forward to Shaunta'e bringing more your way. This is just the beginning.

    

    

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.

    He sifts through over 30,000 survey submissions to uncover the world’s favourite number, and meets a mathematician who looks for universes in his garage. He attends the World Mathematical Congress in India, and visits the engineer who designed the first roller-coaster loop. Get hooked on math as Alex delves deep into humankind’s turbulent relationship with numbers, and reveals how they have shaped the world we live in.

    The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.

    With spendthrift ex Darius back on the scene, she finds herself in a dilemma.Will Sophie fall back into her old ways, or can she find the confidence to make the right decisions and find happiness?

    This book provides an applications-oriented introduction to multivariate data analysis for the non-statistician, by focusing on the fundamental concepts that affect the use of specific techniques.