|Publisher:||CreateSpace Independent Publishing Platform|
|Author:||George A. Duckett|
|Published:||Mar 21 2016|
|Posted:||Jul 23 2016|
|Book size:||5.06 MB|
If you have a question about Data Science this is the book with the answers. Data Science: Questions and Answers takes some of the best questions and answers asked on the datascience.stackexchange.com website. You can use this book to look up commonly asked questions, browse questions on a particular topic, compare answers to common topics, check out the original source and much more. This book has been designed to be very easy to use, with many internal references set up that makes browsing in many different ways possible. Topics covered include: Machine Learning, Bigdata, Data Mining, Classification, Neuralnetwork, Statistics, Python, Clustering, R, Text Mining, NLP, Dataset, Efficiency, Algorithms, Hadoop, SVM, Tools, Recommendation, Visualization, Databases, Feature Selection, NoSQL, K Means, Random Forest, Logistic Regression and many more."
What you need to know about data mining and data-analytic thinking
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. 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 proje...
Using Data Science to Transform Information into Insight
Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And inData Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet....
Building Data Analytics Applications with Hadoop
Mining big data requires a deep investment in people and time. How can you be sure you're building the right models? With this hands-on book, you'll learn a flexible toolset and methodology for building effective analytics applications with Hadoop.Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You'll learn an iterative approach that enables you to quickly change the kind of analysis you're doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps.Create analytics applications by using the agile big data development methodologyBuild valu...
SummaryPractical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the BookBusiness analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day...
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