搜索资源列表
Semi-supervised-learning-NJU
- 半监督学习非常好的一篇文章，机器学习重镇，南京大学写的，希望对大家有所帮助！-Semi-supervised learning is very good article, machine learning center, Nanjing University, write, we want to help!
13Deep-Learning-Tutorial
- 适合机器视觉的深度学习入门讲义，深度学习是机器学习领域现在最热门的领域之一-The deep learning tutorial is suitable to machine vision, which is the most popular area in the machine learning area
Handbook.Of.Research.On.Machine
- 主要讲述机器学习的应用与趋势，包括机器学习的算法，理论算法和新技术，并用实例分析解决现实问题。-Focuses on the application of machine learning and trends, including machine learning algorithms, theory of algorithms and new technologies, and use examples to analyze and solve practical problems.
A-Convex-Feature-Learning
- 国际顶级会议机器学习中的好文章，推荐给做机器学习的同志-paper in international top conference:ICML, strongly recommend it to those working in machine learning
Semsupervised-learning
- 这是一篇关于半监督的论文，半监督学习问题广泛存在于现实世界中, 已经成为目前机器学习和模式识别领域中的一个研究热点. 文章 综述了半监督学习问题的基本思想、研究现状、常用算法及其一些应用领域, 分析了目前存在的主要困难, 并指出需进一步研究的几个问题.-Sem-i supervised learning has been w idely used in the w orld and become a hot topic in the resear ch field of machine
Learning-OpenCV
- 学习openCV的参考代码，有兴趣可以仔细阅读。-Linear machine learning classifier, fitting a linear edge interface code.
Willi-Richert--Luis-Pedro-Coelho-Building-Machine
- Willi Richert, Luis Pedro Coelho Building Machine Learning Systems with Python 2013-Willi Richert, Luis Pedro Coelho Building Machine Learning Systems with Python 2013
Neural-Network_Machine-Learning-Course-Stanford.z
- Matab codes for a simple Neural Network, based on Stanford s Machine Learning online course.
[Hans_Georg_Schaathun(auth.)]_Machine-learning-in
- Machine Learning Book for Beginner
Machine-Learning
- 排序学习算法,排序学习算法 排序学习算法-learning to rank algorithoms
Tutorial-on-Support-Vector-Machine
- Machine Learning is considered as a subfield of Artificial Intelligence and it is concerned with the development of techniques and methods which enable the computer to learn. In simple terms development of algorithms which enable the machine to learn
Statistical-learning-methods
- 该书籍介绍了很好的统计学习方法，能为机器学习和数据挖掘的爱好者提供很好的理论依据。-The book describes the good statistical learning method that can provide a good theoretical basis for machine learning and data mining enthusiasts.
Know-about-Machine-Learning
- 一些关于机器学习算法理论与实现的介绍与实现-a useful things about mechine learning algorism and implemention
machine-l-s-clustering
- machine learning, statistics, clustering
Computational-learning-theory
- wikipedia机器学习迷你书：《Computational learning theory》（计算学习理论） 比较理论，汇集了统计学习理论，VC理论，PAC学习，稳定性，在线学习与分布式学习等基本概念。顺各条参考文献可更深入学习。-wikipedia machine learning mini book: Computational learning theory (calculated learning theory) comparison theory, a collection o
Statistical-Learning
- 一篇机器学习综述，总结了当前机器学习研究的几个方向，并以统计机器学习为重点梳理了几个核心原则。-A document about Machine Learning, focus on Statistic Learning, including four important principle.
Introduction-to-deep-learning
- 深度学习是机器学习最热门的领域,适合机器视觉的深度学习入门讲义-Deep learning is the most popular field of machine learning, suitable for machine vision of deep learning introductory notes
Introduction-to-13deep-learning
- 深度学习是机器学习最热门的领域,适合机器视觉的深度学习-ntroduction to deep learning notes for machine vision, deep learning is now one of the most popular field of machine learning field
Deep-learning-and-new-progress-
- 深度学习是机器学习中的一个新的研究领域。通过深度学习的方法构建深度网络来抽取特征是目 前目标和行为识别中得到关注的研究方向。为引起更多计算机视觉领域研究者对深度学习进行探索和讨论，并推 动目标和行为识别的研究，对深度学习及其在目标和行为识别中的新进展给予概述。方法首先介绍深度学习领 域研究的基本状况、主要概念和原理 然后介绍近期利用深度学习在目标和行为识别应用中的一些新进展。结 果阐述了深度学习与神经网络之间的关系，深度学习的优缺点，以及目前深度学习理论需要解决的主要问题。
Machine-Learning-
- Efficient Learning of Image Super-resolution and Compression Artifact Removal with Semi-Local Gaussian Proce-Efficient Learning of Image Super-resolution and Compression Artifact Removal with Semi-Local Gaussian Process