搜索资源列表
GBDT+SVM
- 使用机器学习中的SVM，GBDT算法构建分类模型，做分类预测。并且对测试结果评估，模型保存。(Use SVM and GBDT algorithm in machine learning to build classification model and do classification prediction. And evaluate the test results and save the model.)
机器学习实战源码
- 《机器学习实战》书的所有源码及数据，python实现！！！
H-ELM
- 可用作数据分类和拟合，深度极限学习机拥有深度学习的优势和自身计算速度快的优势(It can be used to classify and fit data. The deep extrme learning machine has the advantages of depth learning and fast computing speed.)
KELM
- 可用作数据的拟合和分类。核极限学习机采用了核函数，将数据投射到高维空间分类(It can be used for data fitting and classification. Kernel extreme learning machine uses kernel function to project data onto high-dimensional space.)
MATLAB深度学习简介
- 简单的介绍什么是深度学习、深度学习的应用场景等基础知识，帮助我们快速入门该领域(Briefly introduce what is the basic knowledge of deep learning, deep learning application scenarios, and help us quickly get started in this field.)
Machine Learning
- 作者是Prateek Joshi.人工智能专家。本书注重于对基于机器学习中深度学习内容的分析，并附上了许多经典案例，非常值得一读。(The writer is an expert in Prateek Joshi. AI. This book focuses on the analysis of in-depth learning in machine-based learning, and attaches many classic cases, which are worth reading
python machine learning
- 作者是Sebastian Raschka，密歇根州立大学的博士生，他在计算生物学领域提出了几种新的计算方法，还被科技博客Analytics Vidhya评为GitHub上最具影响力的数据科学家。他有一整年都使用Python进行编程的经验，同时还多次参加数据科学应用与机器学习领域的研讨会。在数据科学、机器学习以及Python等领域他拥有丰富的演讲和写作经验，本书可使得不具备机器学习背景的人设计出由数据驱动的解决方案。(The author, Sebastian Raschka, a PhD stu
CAE
- 卷积自编码器，深度学习中的CAE，类似CNN，是深度学习的基本框架之一(Convolution self encoder, CAE in depth learning, similar to CNN, is one of the basic frameworks for deep learning.)
DBN
- 深度信念网络，神经网络的一种。既可以用于非监督学习，类似于一个自编码机；也可以用于监督学习，作为分类器来使用。(Deep belief network, a kind of neural network. It can be used for unsupervised learning, similar to a self-coding machine, or supervised learning, as a classifier.)
uci-breast-cancer-master
- 机器学习中的随机森林算法，用于空气质量预测(Random forest algorithm in machine learning for air quality prediction)
TrAdaboost
- 迁移学习中经典算法Tradaboost的python实现(Python implementation of classical algorithm Tradaboost in transfer learning)
Andrew Ng machine-learning-ex4
- 吴恩达机器学习课程源码，第4个练习作业代码(Andrew machine learning course source code, the fourth practice code)
maantdlence
- 这是关于kalman的程序,对学习kalman的人会有一定的帮助(This is a program about kalman, which will be of some help to people who learn about kalman.)
Inception_V3(Transfer)
- 本算法实现了InceptionV3模型的迁移学习。训练好的inceptionV3模型可自行搜索下载.pb文件，数据集需为本地jpg图片。(Realization of full adder schematic diagram)
ELM_linbo.jin
- 极限学习机的代码，机器学习，可以用于分类等.(Extreme learning machine used in classification)
1D-CNN
- 一维信号的深度学习算法和例子包括CNN、DBN等，有详细的说明(Deep Learning Algorithms and Examples for One-Dimensional Signals)
迁移学习工具箱
- 迁移学习通用工具箱，亲测好用！里面包含很多迁移学习有关算法！
Deep learning tensorboard
- 这个一个人工智能中深度学习下的网络查看源码Tensorboard，网络运行过程中，通过对该代码的查看，可以及时了解网络性能，便于调节网络结构、参数等。
MEDA
- 目前 看到效果最好的 文章 迁移学习，文章：Visual Domain Adaptation with Manifold Embedded Distribution Alignment ，王晋东(Probably,the most effective article transfer learning,Visual Domain Adaptation with Manifold Embedded Distribution Alignment , Wang ji dong)
LLE-master
- 流形学习局部线性嵌入算法MATLAB实现源代码(Manifold Learning Local Linear Embedding Algorithms MATLAB Implementation Source Code)