Algorithm Research Papers

WEKA: a machine learning workbench

WEKA is a workbench for machine learning that is intended to aid in the application of machine learning techniques to a variety of real-world problems, in particular, those arising from agricultural and horticultural domains. Unlike other m...

Machine Learning

Practical Machine Learning with Python

This book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, desi...

Pattern Recognition and Machine Learning

A State-of-the-Art Review on Machine Learning-based Methods for Prostate Cancer Diagnosis

Prostate cancer can be viewed as the second most dangerous and diagnosed cancer of men all over the world. In the past decade, machine and deep learning methods play a significant role in improving the accuracy of classification for both bi...

Machine Learning in Economics and Finance

Machine Learning Algorithms - A Review

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without being explicitly programmed. Learning algorithms in many applications that's we make use of dail...

Pattern Recognition and Machine Learning

The learning machine: Learning

Adaptive Computation and Machine Learning

An introduction to quantum machine learning

Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT...

Genetic Algorithms in Search, Optimization and Machine Learning

David Goldberg's Genetic Algorithms in Search, Optimization and Machine Learning is by far the bestselling introduction to genetic algorithms. Goldberg is one of the preeminent researchers in the field--he has published over 100 research ar...

Pattern Recognition and Machine Learning, 2006

Proceedings of the 25th international conference on Machine learning

This volume contains the papers accepted to the 25th International Conference on Machine Learning (ICML 2008). ICML is the annual conference of the International Machine Learning Society (IMLS), and provides a venue for the presentation and...

Machine Learning With Python

In previous chapters, we saw what artificial intelligence is and how machine learning and deep learning techniques are used to train machines to become smart. In these next few chapters, we will learn how machines are trained to take data, ...

Artificial intelligence, machine learning and deep learning

It is increasingly recognized that artificial intelligence has been touted as a new mobile. Because of the high volume of data that being generated by devices, sensors and social media users, the machine can learn to distinguish the pattern...

Machine Learning: A Bayesian and Optimization Perspective

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabil...

Applied Machine Learning

A First Course in Machine Learning

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations ...

Machine Learning for Evolution Strategies