搜索资源列表
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- python scikit-learn lshforest的使用-use lshforest
py_ml
- 简单的人脸识别，及其他机器学习方法，使用scikit-learn。-machine learning using python
test1
- scikit-learn常用分类器的实例-Examples of commonly used scikit-learn classifier
Scikit-learn_handbook
- Scikit-learn 使用手册中文版-Scikit-learn handbook
scikit-learn-docs
- 学习机器学习的利器，非常适合初学者，书写的十分详细(Learning machine learning tool)
Hands_on_ML
- 很棒的入门向机器学习/数据科学的图书，基于scikit learn和TensorFlow库，手把手叫你如何上手机器学习，如何做数据挖掘。(the Best seller In American Amazon. With this book, you can learn a lot about how to use sklean and Tensorflow, in addition, you can have a practical understanding on the whole mach
用Python做科学计算
- 利用python语言以及Numpy，Scipy,Pandas,scikit-learn等库进行科学计算。(Using Python language and Numpy, Scipy, Pandas, scikit-learn and other libraries for scientific computing.)
handson-ml-master
- 这个项目的目的是教你机器学习的基本原理。它包含了Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的示例代码和解决方案。非常好的一本书！(This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code and solutions to the exercises in
scikit-learn-master
- 用python学习scikit-learn(Learning scikit-learn with Python)
scikit-learn-master02
- 用python学习scikit-learn 02(Learning scikit-learn with Python 02)
scikit-learn-master03
- 用python学习scikit-learn 03(Learning scikit-learn with Python 03)
scikit-learn-04
- 用python学习scikit-learn 04(Learning scikit-learn with Python 04)
s-l5
- 用python学习scikit-learn 05(Learning scikit-learn with Python 05)
sl
- 用python学习scikit-learn 01(Learning scikit-learn with Python 01)
CART
- 对汽车评估的分类决策树构建,使用了常用的python的机器学习库scikit-learn(Construction of classified decision tree for automobile evaluation,Use the common Python's machine learning library scikit-learn)
Scikit-Learn与TensorFlow机器学习实用指南
- Scikit-Learn与TensorFlow机器学习实用指南(Scikit-Learn and TensorFlow machine learning practical guide)
scikit-learn-doc-zh-0.19.X
- 这是我收集的比较好的scikit-learn学习资料(This is the better scikit-learn learning material I have collected)
sklearn-tree-BN-knn
- 分类器的性能比较与调优: 使用scikit-learn 包中的tree，贝叶斯，knn，对数据进行模型训练，尽量了解其原理及运用。 使用不同分析三种分类器在实验中的性能比较，分析它们的特点。 本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the dat
机器学习实战：基于Scikit-Learn和TensorFlow
- 基于scikit-learn和tensorflow的机器学习实战教程(Machine Learning Practical Course)