Machine Learning Approach

Intrusion Detection: A Machine Learning Approach, Volume 3

Intrusion Detection: A Machine Learning Approach, Volume 3 (Series in Electrical and Computer Engineering) by Zhenwei Yu and Jeffrey J P Tsai
English | 2011 | ISBN: 1848164475 | 184 pages | PDF | 1 MB
Rule Based Systems for Big Data: A Machine Learning Approach (Repost)

Han Liu, Alexander Gegov, Mihaela Cocea, "Rule Based Systems for Big Data: A Machine Learning Approach"
English | 2015 | ISBN-10: 3319236954 | 121 pages | pdf | 2.8 MB
Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series) [Repost]

Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series) by Pierre Baldi
English | 10 Aug. 2001 | ISBN: 026202506X | 400 Pages | PDF | 3.29 MB

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules.

Pierre Baldi, Bioinformatics: The Machine Learning Approach  

Posted by Direktor69 at July 18, 2013
Pierre Baldi, Bioinformatics: The Machine Learning Approach

Pierre Baldi, Bioinformatics: The Machine Learning Approach
ISBN: 026202506X | edition 2001 | PDF | 477 pages | 6 mb

Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students. First are the biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function. Second are those with a primary background in physics, mathematics, statistics, or computer science who need to know more about specific applications in molecular biology

Bioinformatics: The Machine Learning Approach, 2nd Edition  eBooks & eLearning

Posted by SweetStroke at Aug. 16, 2006
Bioinformatics: The Machine Learning Approach, 2nd Edition

Pierre Baldi, Søren Brunak, «Bioinformatics: The Machine Learning Approach, 2nd Edition»
The MIT Press | ISBN 026202506X | 2001 Year | PDF | 5,94 Mb | 400 Pages

"Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students. First are the biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function. Second are those with a primary background in physics, mathematics, statistics, or computer science who need to know more about specific applications in molecular biology."

R Machine Learning solutions  eBooks & eLearning

Posted by naag at Dec. 10, 2016
R Machine Learning solutions

R Machine Learning solutions
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 8.5 Hours | 1.81 GB
Genre: eLearning | Language: English

R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics. This video course will take you from very basics of R to creating insightful machine learning models with R. You will start with setting up the environment and then perform data ETL in R.

R: Recipes for Analysis, Visualization and Machine Learning  eBooks & eLearning

Posted by AlenMiler at Dec. 9, 2016
R: Recipes for Analysis, Visualization and Machine Learning

R: Recipes for Analysis, Visualization and Machine Learning by Viswa Viswanathan
English | 24 Nov. 2016 | ASIN: B01N7AE091 | 959 pages | AZW3/MOBI/EPUB/PDF (conv) | 111.63 MB

Get savvy with R language and actualize projects aimed at analysis, visualization and machine learning
Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI

Practical Machine Learning with H20: Powerful, Scalable Techniques for Deep Learning and AI by Darren Cook
English | 31 Dec. 2016 | ISBN: 149196460X | 300 Pages | AZW3/MOBI/EPUB/PDF (conv) | 17.61 MB

In Practical Machine Learning with H2O, author Darren Cook introduces readers to H2O, an open-source machine learning package that is gaining popularity in the data science community.

Python for Probability, Statistics, and Machine Learning  eBooks & eLearning

Posted by Underaglassmoon at March 25, 2016
Python for Probability, Statistics, and Machine Learning

Python for Probability, Statistics, and Machine Learning
Springer | Signals & Communication | April 11, 2016 | ISBN-10: 3319307150 | 276 pages | pdf | 7.1 mb

Authors: Unpingco, José
Explains how to simulate, conceptualize, and visualize random statistical processes and apply machine learning methods
Connects to key open-source Python communities and corresponding modules focused on the latest developments in this area
Outlines probability, statistics, and machine learning concepts using an intuitive visual approach, backed up with corresponding visualization codes
Machine Learning for Adaptive Many-Core Machines - A Practical Approach

Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data) by Noel Lopes and Bernardete Ribeiro
English | 2014 | ISBN: 3319069373, 331906939X | 241 pages | Epub (conv) | 7.77 MB