搜索资源列表
EM-learning
- 一个em学习的matlab例程，可以直接运行，具体内容参考图书《视觉机器学习20讲》-A EM learning matlab routines, you can run directly, the specific content of reference books < visual machine learning 20
Siemens-learning-materials
- Siemens learning materials
Java-learning-courseware
- Java learning courseware
bayesian-learning
- 贝叶斯学习和强化学习相结合，其中包含贝叶斯Q学习-bayesian learning combined with reinforcement learning
GUI-Learning
- this is for gui matlab learning
Machine-Learning-in-Action
- This the python code according to the book named machine learning in action.-This is the python code according to the book named machine learning in action.
machine-learning-ex2-8
- 斯坦福机器学习网上公开课相关编程练习代码，包括线性回归，逻辑回归，神经网络，PCA,SVM等。-the programming code of online course Mechine Learning provided by Stanford.
My-learning-summray-for-power-system
- 电力系统学习小结，个人理解，希望对大家 有帮助。-My learning summary for power system
Learning-Library-for-PHP-master
- it is a machine learning for PHP.
awesome-machine-learning-master
- this code about mashin learning
Learning-to-Detect-a-Salient-Object
- Learning to Detect a Salient Object 文章的代码实现-Learning to Detect a Salient Object code article
machine-learning
- 最小二乘学习算法,对函数进行拟合，核函数为三角函数，减小过拟合现象-Least square learning algorithm of translation
Deep.Learning.Yann.LeCun
- 基于深度学习Deep Learning的相关研究与介绍，其中涵盖caffe 等开发平台的原理介绍-Based on the Deep Learning Deep Learning related research and introduction, which covers the development platform caffe and other principles introduced
Li-Hang-Machine-learning-process
- 李航博士的机器学习过程，以及对机器学习中的各类算法点评，很实用。-Dr. Li Hang Machine learning process, as well as various types of machine learning algorithms reviews, very practical.
ExerciseSelf-Taught-Learning
- Soft-taught leaning是用的无监督学习来学习到特征提取的参数，然后用有监督学习来训练分类器.-Soft-taught leaning unsupervised learning is to learn the parameters of feature extraction, followed by supervised learning to train the classifier.
Machine-Learning-in-Python
- 《Python机器学习及实践：从零开始通往Kaggle竞赛之路》源码，提供了一些流行的机器学习框架与程序库的应用实例，包括tensorflow框架，注重实战。-Python machine learning and practice: zero to the road leading to the Kaggle contest source code, provides some popular machine learning framework and application examp
machine--Learning-concept
- 机器学习(Machine Learning, ML)是一门多领域交叉学科，涉及概率论、统计学、逼近论、凸分析、算法复杂度理论等多门学科。专门研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技能，重新组织已有的知识结构使之不断改善自身的性能。 它是人工智能的核心，是使计算机具有智能的根本途径，其应用遍及人工智能的各个领域，它主要使用归纳、综合而不是演绎。-Machine Learning (Machine Learning, ML) is more than one field of
Q-Learning-Example-1
- Q-学习是一种重要的强化学习方法，提供一个Q-学习做路径规划的例子，初学者可以通过代码学习Q-学习的原理。-Q- learning is an important reinforcement learning methods, to provide an example of Q- learning to do path planning, beginners can learn the principles of Q- code.
Reinforcement-Learning
- 基于神经网络的强化学习是对强化学习算法的一种改进，本文讲述了将基于神经网络的强化学习算法用于移动机器人动态导航。-Reinforcement learning based on neural network is an improvement of reinforcement learning algorithm. This paper describes the reinforcement learning algorithm based on neural network for dynam
ensemb-learning
- 处理非平衡问题的集成方法，基于随机森林的集成学习-Ensemble learning method,which is based on the random forest classifier, to deal with data imbalance problem