If you're an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. You'll learn how to write algorithms that automatically sort and redirect email based on statistical patterns. Authors Drew Conway and John Myles White approach the process in a practical fashion, using a case-study driven approach rather than a traditional math-heavy presentation.
This book also includes a short tutorial on using the popular R language to manipulate and analyze data. You'll get clear examples for analyzing sample data and writing machine learning programs with R.
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Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.
John Myles White is a Ph.D. student in the Princeton Psychology Department, where he studies how humans make decisions both theoretically and experimentally. Outside of academia, John has been heavily involved in the data science movement, which has pushed for an open source software approach to data analysis. He is also the leadmaintainer for several popular R packages, including ProjectTemplate and log4r.
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Da: Scissortail, Oklahoma City, OK, U.S.A.
Condizione: good. This is a pre-loved book that shows moderate signs of wear from previous reading. You may notice creases, edge wear, or a cracked spine, but it remains in solid, readable condition.Please note:-May include library or rental stickers, stamps, or markings.-Supplemental materials e.g., CDs, access codes, inserts are not guaranteed.-Box sets may not come with the original outer box. If it does, the box will not be in perfect condition. -Sourced from donation centers; authenticity not verified with publisher. Your satisfaction is our top priority! If you have any questions or concerns about your order, please don't hesitate to reach out. Thank you for shopping with us and supporting small businessâ"happy reading! Codice articolo STM.41M
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Da: WorldofBooks, Goring-By-Sea, WS, Regno Unito
Paperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Codice articolo GOR009374166
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 13356267
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 13356267-n
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Da: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo WO-9781449314309
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo WO-9781449314309
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Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Machine Learning for Email: Spam Filtering and Priority Inbox. Book. Codice articolo BBS-9781449314309
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Da: Rarewaves USA, OSWEGO, IL, U.S.A.
Paperback. Condizione: New. This compact book explores standard tools for text classification, and teaches the reader how to use machine learning to decide whether a e-mail is spam or ham (binary classification), based on raw data from The SpamAssassin Public Corpus. Of course, sometimes the items in one class are not created equally, or we want to distinguish among them in some meaningful way. The second part of the book will look at how to not only filter spam from our email, but also placing "more important" messages at the top of the queue. This is a curated excerpt from the upcoming book "Machine Learning for Hackers.". Codice articolo LU-9781449314309
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLIING23Mar2411530330221
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Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9781449314309
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