Industry experts Jacqueline Nolis and Emily Robinson lay out the soft skills you’ll need alongside your technical know-how in order to succeed in the field. Following their clear and simple instructions you’ll craft a resume that hiring managers will love, learn how to ace your interview, and ensure you hit the ground running in your first months at your new job. Once you’ve gotten your foot in the door, learn to thrive as a data scientist by handling high expectations, dealing with stakeholders, and managing failures. Finally, you’ll look towards the future and learn about how to join the broader data science community, leaving a job gracefully, and plotting your career path. With this book by your side you’ll have everything you need to ensure a rewarding and productive role in data science.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

    Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

    This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"

    It combines the nice features of a scripting language with the powerful features of a production environment—features like persistent data structures and clean multithreading that you'll need for industrial-strength application development.The Joy of Clojure goes beyond just syntax to show you how to write fluent and idiomatic Clojure code. You'll learn a functional approach to programming and will master Lisp techniques that make Clojure so elegant and efficient. The book gives you easy access to hard soft ware areas like concurrency, interoperability, and performance. And it shows you how great it can be to think about problems the Clojure way. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's InsideThe what and why of ClojureHow to work with macrosHow to do elegant application designFunctional programming idiomsWritten for programmers coming to Clojure from another programming background—no prior experience with Clojure or Lisp is required.