Fundamentals Machine Learning Predictive

Machine learning Predictive Analytics Report  eBooks & eLearning

Posted by AlenMiler at Sept. 2, 2016
Machine learning Predictive Analytics Report

Machine learning PREDICTIVE ANALYTICS REPORT by Gerard Blokdijk
English | 27 Aug 2016 | ASIN: B01L643B4A | 96 Pages | MOBI | 20.09 MB

The Machine learning report evaluates technologies and applications in terms of their business impact, adoption rate and maturity level to help users decide where and when to invest.
Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies By John D. Kelleher
2015 | 624 Pages | ISBN: 0262029448 | EPUB | 7 MB
Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies by John D. Kelleher
English | July 24, 2015 | ISBN: 0262029448 | 624 Pages | AZW3/PDF (conv) | 24 MB

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification.

Learning From Data - Introductory Machine Learning Course  eBooks & eLearning

Posted by FenixN at Nov. 28, 2016
Learning From Data - Introductory Machine Learning Course

Learning From Data - Introductory Machine Learning Course
HDRips | MP4/AVC, ~222 kb/s | 1280x720 | Duration: 23:36:03 | English: AAC, 96 kb/s (2 ch) | 3.22 GB
Genre: Science

This introductory computer science course in machine learning will cover basic theory, algorithms, and applications. Machine learning is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. Machine learning has become one of the hottest fields of study today and the demand for jobs is only expected to increase. Gaining skills in this field will get you one step closer to becoming a data scientist or quantitative analyst.

An Introduction to Machine Learning with Web Data [repost]  eBooks & eLearning

Posted by FenixN at Nov. 28, 2016
An Introduction to Machine Learning with Web Data [repost]

An Introduction to Machine Learning with Web Data
HDRips | MP4/AVC, ~1200 kb/s | 1280x720 | Duration: 02:43:22 | English: AAC, 128 kb/s (2 ch) | 1.43 GB
Genre: Development / Programming

Once you've accumulated a pile of data through your web application, what do you do with it? In this insightful video course, bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. You'll follow several examples through the entire process—from obtaining, cleaning, and exploring data to building a model and interpreting the results.

Python Machine Learning Solutions  eBooks & eLearning

Posted by FenixN at Nov. 25, 2016
Python Machine Learning Solutions

Python Machine Learning Solutions
HDRips | MP4/AVC, ~461 kb/s | 1280x720 | Duration: 04:27:23 | English: AAC, 128 kb/s (2 ch) | 1.05 GB
Genre: Development / Programming

100 videos that teach you how to perform various machine learning tasks in the real world.

Learning Path: Machine Learning  eBooks & eLearning

Posted by FenixN at Nov. 21, 2016
Learning Path: Machine Learning

Learning Path: Machine Learning
HDRips | MP4/AVC, ~1440 kb/s | 1920/1080 | 1280x720 | Duration: 23:52:47 | English: AAC, 128 kb/s (2 ch)
Size: 21.8 GB | Genre: Development / Programming

With the growing prominence of data science and its uses across all types of business, it's the perfect time to start applying machine learning. In this Learning Path, you'll master everything you need to transform data into action. Start with basic techniques and move on to coding your own machine learning algorithms.
Machine Learning in Medical Imaging: Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, Franc

Machine Learning in Medical Imaging: Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, … Papers
English | November 13, 2012 | ISBN: 3642354270| 287 Pages | PDF | 21 MB

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012.
Machine Learning in Medical Imaging: Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, C

Machine Learning in Medical Imaging: Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, …
English | September 13, 2011 | ISBN: 3642243185 | 388 Pages | PDF | 10 MB

This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning in Medical Imaging, M.L.M.I. 2011, held in conjunction with M.I.C.C.A.I. 2011, in Toronto, Canada, in September 2011.
Machine Learning in Medical Imaging: First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, Ch

Machine Learning in Medical Imaging: First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings
English | September 3, 2010 | ISBN: 3642159478 | 199 Pages | PDF | 5 MB

The first International Workshop on Machine Learning in Medical Imaging, MLMI 2010, was held at the China National Convention Center, Beijing, China on September 20, 2010 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2010. Machine learning plays an essential role in the medical imaging field, including image segmentation, image registration, computer-aided diagnosis, image fusion, image- guided therapy, image annotation, and image database retrieval. With advances in medical imaging, new imaging modalities, and methodologies such as cone-beam/multi-slice CT, 3D Ultrasound, tomosynthesis, diffusion-weighted MRI, electrical impedance to- graphy, and diffuse optical tomography, new machine-learning algorithms/applications are demanded in the medical imaging field.