Semi Supervised And Unsupervised Machine Learning

Semi-Supervised and Unervised Machine Learning: Novel Strategies (Repost)  eBooks & eLearning

Posted by advisors at Dec. 25, 2014
Semi-Supervised and Unervised Machine Learning: Novel Strategies (Repost)

Semi-Supervised and Unervised Machine Learning: Novel Strategies By Amparo Albalate, Wolfgang Minker
2011 | 244 Pages | ISBN: 1848212038 | PDF | 69 MB

Semi-Supervised and Unervised Machine Learning: Novel Strategies  eBooks & eLearning

Posted by enmoys at Oct. 28, 2013
Semi-Supervised and Unervised Machine Learning: Novel Strategies

Semi-Supervised and Unervised Machine Learning: Novel Strategies By Amparo Albalate, Wolfgang Minker
2011 | 244 Pages | ISBN: 1848212038 | PDF | 69 MB

Unsupervised Machine Learning in Python  eBooks & eLearning

Posted by arundhati at July 7, 2016
Unsupervised Machine Learning in Python

LazyProgrammer, "Unsupervised Machine Learning in Python: Master Data Science and Machine Learning with Cluster Analysis, Gaussian Mixture Models, and Principal Components Analysis"
2016 | ASIN: B01G1HH5T4 | 56 pages | EPUB | 1 MB

Introduction to Computer Science and Programming using Python  eBooks & eLearning

Posted by ParRus at April 28, 2016
Introduction to Computer Science and Programming using Python

Introduction to Computer Science and Programming using Python
WEBRip | English | MKV + Project files | 640 x 360 | AVC ~430 kbps | 29.970 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | 32h 34mn | 11.89 GB
Genre: Video Tutorial / Computer Science, Development, Programming

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.

Introduction to Computer Science and Programming using Python (Repost)  eBooks & eLearning

Posted by Polik88 at Sept. 27, 2014
Introduction to Computer Science and Programming using Python (Repost)

Introduction to Computer Science and Programming using Python (Repost)
English | MP4 | 640x480 | AVC 768 Kbps 29.970 fps | AAC 80 Kbps 44.1 khz | 32h 34mn | 7.8 GB
Sample Files: present
Genre: Video Training

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.

Kernel Based Algorithms for Mining Huge Data Sets (Repost)  eBooks & eLearning

Posted by lenami at Nov. 21, 2010
Kernel Based Algorithms for Mining Huge Data Sets (Repost)

Kernel Based Algorithms for Mining Huge Data Sets
Publisher: Springer | ISBN: 3540316817 | edition 2006 | PDF | 260 pages | 5 mb

"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets by using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction (feature elimination) and shows the similarities and differences between the two most popular unsupervised techniques, the principal component analysis (PCA) and the independent component analysis (ICA). The book presents various examples, software, algorithmic solutions enabling the reader to develop their own codes for solving the problems. The book is accompanied by a website for downloading both data and software for huge data sets modeling in a supervised and semisupervised manner, as well as MATLAB based PCA and ICA routines for unsupervised learning. The book focuses on a broad range of machine learning algorithms and it is particularly aimed at students, scientists, and practicing researchers in bioinformatics (gene microarrays), text-categorization, numerals recognition, as well as in the images and audio signals de-mixing (blind source separation) areas.
Supervised and Unsupervised Pattern Recognition: Feature Extraction and Computational Intelligence [Repost]

Supervised and Unsupervised Pattern Recognition: Feature Extraction and Computational Intelligence (Industrial Electronics) by Evangelia Miche Tzanakou
English | Dec 28, 1999 | ISBN: 0849322782 | 367 Pages | PDF | 16 MB

There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images.

Reinforcement and Systemic Machine Learning for Decision Making [Repost]  eBooks & eLearning

Posted by ChrisRedfield at Jan. 9, 2015
Reinforcement and Systemic Machine Learning for Decision Making [Repost]

Parag Kulkarni - Reinforcement and Systemic Machine Learning for Decision Making
Published: 2012-08-14 | ISBN: 047091999X | PDF | 312 pages | 2 MB

Reinforcement and Systemic Machine Learning for Decision Making (repost)  eBooks & eLearning

Posted by interes at June 21, 2014
Reinforcement and Systemic Machine Learning for Decision Making (repost)

Reinforcement and Systemic Machine Learning for Decision Making by Parag Kulkarni
English | ISBN: 047091999X | 2012 | 312 pages | PDF | 3 MB

Reinforcement and Systemic Machine Learning for Decision Making explores a newer and growing avenue of machine learning algorithm in the area of computational intelligence.

Supervised and Unsupervised Ensemble Methods and their Applications [Repost]  eBooks & eLearning

Posted by ChrisRedfield at Oct. 8, 2013
Supervised and Unsupervised Ensemble Methods and their Applications [Repost]

Oleg Okun, ‎Giorgio Valentini - Supervised and Unsupervised Ensemble Methods and their Applications
Published: 2008-04-18 | ISBN: 3540789804 | PDF | 180 pages | 3 MB