andrew ng machine learning python

K-means Clustering algorithm Test: #-*-coding:utf-8-*-"""Created on Thu 10:59:20 2017@author:administrator"""" "There are eight major variable data on the average annual consumer spending of urban households in 31 provinces in 1999, with eight variables: food, clothing, household equipment supplies and services, health care, transportation and communications, cultural services for recreational education, residential and miscellaneous goods and services. The 31 provinces are c

The language used for machine learning is python. Here's how to get started with Python for "machine learning." (Environment: CentOS 7)1, two important packagesNumPy and SciPy. (http://scipy.org/scipylib/download.html) mainly deal

1. Background In the future, the blogger will update the machine learning algorithm and its Python simple implementation regularly every week. Today's algorithm is the KNN nearest neighbor algorithm. KNN algorithm is a kind of supervised learning classifier class algorithm. What is supervised

Here is still to recommend my own built Python development Learning Group: 483546416, the group is the development of Python, if you are learning Python, small series welcome you to join, everyone is the software Development Party, not regularly share dry goods (only

you separate a room with a wall, you're trying to create two different populations in the same room. Similarly, decision trees are dividing the population into different groups as much as possible. For more information, see: Simplification of decision tree algorithms Python code 7, K mean value algorithm k– mean algorithm is a kind of unsupervised learning algorithm, it can solve the problem of clustering.

), though it's no better than Microsoft's Visual Studio, but it's much more than the one that comes with it-if it's written in C, Helpless is written in Java, startup speed huge slow ~ ~Recently turned over the book "Machine Learning in Action". The book uses Python to implement some machine

[Email protected]:~# pip Install-u Scikit-learnNo problemSuccessfully installed scikit-learncleaning up ...Other workarounds see: http://www.xuebuyuan.com/1157602.htmlInstalling NETWORKXwget https://pypi.python.org/packages/source/n/networkx/networkx-1.10.tar.gz#md5= EB7A065E37250A4CC009919DACFE7A9DCD Networkx-1.10python setup.py InstallTest it:[Email protected]:~/networkx-1.10# pip listmatplotlib (1.3.1) networkx (1.10) numpy (1.8.2) pip (1.5.4) Scikit-learn ( 0.16.1) scipy (0.13.3) setuptools

Python Machine Learning Practical tutorialsShare Network address--https://pan.baidu.com/s/1miib4og Password: WTIWThe course is really good, share to everyoneMachine Learning (machines learning, ML) is a multidisciplinary interdisciplinary subject involving probability theory

the data after dimensionality reduction -Pca_svc =linearsvc () the #Learning - Pca_svc.fit (Pca_x_train, Y_train)WuyiPca_y_predict =pca_svc.predict (pca_x_test) the - #4 Model Evaluation Wu Print("accuracy of raw data:", Svc.score (X_test, y_test)) - Print("other ratings: \ n", Classification_report (Y_test, Y_predict, Target_names=np.arange (10). Astype (str ))) About $ Print("data accuracy rate after dimensionality reduction:", Pca_svc.score (Pca

1. Install Pipmkdir ~/vi ~/.pip/pip.conf[global]trusted-host=mirrors.aliyun.comindex -url=http://https://bootstrap.pypa.io/get-pip.pysudo python get---9.0. 1 from/usr/local/lib/python2. 7 2.7)2. Install the Machine learning PackageThe following installation package is not chaotic due to dependenciessudo Install sudo install sudo install sudo install scipyError:S

============================================================================================ "Machine Learning Combat" series blog is Bo master reading " Machine learning Combat This book's notes, including the understanding of the algorithm and the Python code implementatio

as the similarity of two vectors.The commonly used kernel functions are: Polynomial cores: , which is the threshold value, is the index set by the user. Hyperbolic tangent (sigmoid) Cores: Radial basis function core (Gaussian core): Now summarize the steps of the nuclear PCA, taking the RBF nucleus as an example:1 compute the kernel (similarity) matrix K, which is the calculation of any two training samples:Get K:For example, if the training set has 10

This article describes the python Machine Learning Decision tree in detail (demo-trees, DTs) is an unsupervised learning method for classification and regression. Advantages: low computing complexity, easy to understand output results, insensitive to missing median values, and the ability to process irrelevant feature