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Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition James D. Miller, Rui Miguel Forte

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition James D. Miller, Rui Miguel Forte - okladka książki

Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition James D. Miller, Rui Miguel Forte - okladka książki

Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition James D. Miller, Rui Miguel Forte - audiobook MP3

Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition James D. Miller, Rui Miguel Forte - audiobook CD

Autorzy:
James D. Miller, Rui Miguel Forte
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
448
Dostępne formaty:
     PDF
     ePub
     Mobi
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.

The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks.

By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R.

Wybrane bestsellery

O autorach książki

James D. Miller is an IBM certified expert, Master Consultant, Application/System Architect with +35 years of applications & system design/development experience across multiple platforms, technologies and data formats, including Big Data.

His experience includes IBM Planning Analytics, BI, Web architecture & design, systems analysis, GUI design & testing, Data modeling, design, and development of OLAP, Client/Server, Web & Mainframe applications and systems utilizing: Planning Analytics Workspace (PAW), IBM Watson Analytics, Cognos BI & TM1, Framework Manager, dynaSight/ArcPlan, ASP, DHTML, XML, MS Visual Basic, VBA, PERL, R, SPLUNK, MS SQL Server, ORACLE, etc.

He has authored numerous books, including Implementing Splunk - Second Edition; Mastering Splunk; Hands-On Machine Learning with IBM Watson; IBM Watson Projects; Statistics for Data Science; Mastering Predictive Analytics with R - Second Edition and others.

Project areas include those with Data Analytics, Planning Analytics, and FOPM projects, holding various roles from architect, developer, technical and project leader.
Why do you think this reviewer is suitable for this book?



Mr. Rui Miguel Forte has authored a book for Packt titled “Mastering Predictive Analytics with R”. The book has received a 5 star rating. He has 3 years experience as a Data Scientist. He has knowledge of Scala, Python, R, PHP.



• Has the reviewer published any articles or blogs on this or a similar tool/technology ? [Provide Links and References]



A brief of Unsupervised learning has been covered in his book “Mastering Predictive Analytics with R”



https://www.safaribooksonline.com/library/view/mastering-predictive-analytics/9781783982806/



https://www.linkedin.com/profile/view?id=AAkAAAC5YUIBYL7LyLCWZ6LsR0ENJxByC2jU9AU&authType=NAME_SEARCH&authToken=c1Pg&locale=en_US&trk=tyah&trkInfo=clickedVertical%3Amynetwork%2CclickedEntityId%3A12149058%2CauthType%3ANAME_SEARCH%2Cidx%3A1-1-1%2CtarId%3A1444032603690%2Ctas%3ARui%20Miguel%20Forte





• Feedback on the Outline (in case outline has been shared with the reviewer)



The author said the outline is good to go.



• Did the reviewer share any concerns or questions regarding the reviewing process? (related to the schedule, commitment, or any additional comments)



No

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