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Programming Libraries Programming Library ResourcesI am an advocate of the concept of "learning to be adventurous and try." This is the way I learn programming, I believe many people also learn to program design. First understand your ability limits, then expand your ability. If you know how to program, you can draw on the experience of programming quickly to learn more about machine
a machine learning course at Stanford University. Take more course notes, complete course assignments as much as possible, and ask more questions.
Read some books: This refers not to textbooks, but to the books listed above for beginners of programmers.
Master a tool: Learn to use an analysis tool or class library, such as the python Machine
There is a period of time does not dry goods, home are to be the weekly lyrics occupied, do not write anything to become salted fish. Get to the point. The goal of this tutorial is obvious: practice. Further, when you learn some knowledge about machine learning, how to deepen the understanding of the content through practice. Here, we make an example from the 2nd
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2. How to classify real samples:
Iris DataSet, which is a very classic dataset, Scikit-learn the Basic sample datasets commonly used in tutorial. This paper focuses on the cross-validation (Zhouhuazhi-machine learning, which is a good summary of the model evaluation). Error: Training error, test error, generalization error. Our ultimate goal
. Important modules of machine learning
The most important modules of machine learning are NumPy, Pandas, Matplotlib, and IPython. One book covers some of the modules: Data Pipeline Analysis Platform with Open Source pipeline Tools. Then from 1. the free book "Introduction functions to develop Python functions for econ
package based on celery and Elasticsearch.
Thanks to Weibo friends @ the spring of the great hillside provides clues: Our group colleagues previously released Xtas, also Python-based text mining Toolkit, welcome to use, Link: http://t.cn/RPbEZOW. Look good, look back and try it.GitHub code page: Https://github.com/NLeSC/xtasThird, the Python Scientific Computing ToolkitSpeaking of scientific calculation, we first think of MATLAB, set numerical c
images in Python, which has a pretty good effect.
SVG chart builder in pygal-Python.
Pycascading
Miscellaneous scripts/ipython notes/code library
Pattern_classification
Thinking stats 2
Hyperopt
Numpic
2012-paper-diginorm
Ipython-notebooks
Demo-weights
Sarah Palin lda-Sarah Palin's email about topic modeling.
Diffusion segmentation-a set of image segmentation algorithms based on the diffusion method.
Scipy tutorials-scipy tutorial. It is
Hyperopt
Numpic
2012-paper-diginorm
Ipython-notebooks
Demo-weights
Sarah Palin lda-Sarah Palin's email about topic modeling.
Diffusion segmentation-a set of image segmentation algorithms based on the diffusion method.
Scipy tutorials-scipy tutorial. It is out of date. Please refer to scipy-lecture-notes
Crab-Python recommendation engine library.
Bayesian inference tool in bayespy-Python.
Scikit-learn tutorials-scikit-learn
Azure Machine Learning ("AML") is a Web-based computer learning service that Microsoft has launched on its public cloud azure, a branch of AI that uses algorithms to make computers recognize a large number of mobile datasets. This approach is able to predict future events and behaviors through historical data, which is significantly better than traditional forms
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2. How to classify real samples:
Iris DataSet, which is a very classic dataset, Scikit-learn the Basic sample datasets commonly used in tutorial. This paper focuses on the cross-validation (Zhouhuazhi-machine learning, which is a good summary of the model evaluation). Error: Training error, test error, generalization error. Our ultimate goal
programming, I believe many people also learn to program design. First understand your ability limits, then expand your ability. If you know how to program, you can draw on the experience of programming quickly to learn more about machine learning. Before you implement a real-world product system, you must follow some rules and learn the relevant mathematical knowledge.Find a library and read the documenta
Schematic diagram of Java Virtual Machine 1.4 field table set in the class file -- how the field is organized in the class file, graphic tutorial on Virtual Machine networking0. Preface
Understanding the principles of JVM virtual machines is the only way for every Java programmer to practice. However, the JVM virtual machine
From http://www.infoq.com/cn/news/2014/07/pycon-2014This year's Pycon was held in Montreal, Canada on April 9, and Python has been widely used in academia thanks to its rapid prototyping capabilities. The recent official website has released videos and slideshows of the General Assembly tutorial section, including a number of (nearly half) content related to data mining and machine
we invent a new learning model or algorithm, then cross-validation can be used to evaluate the model. In NLP, for example, we focus our training on part of the training and part of the test.Reference documents[1] machine learning Open Class by Andrew Ng in Stanford http://openclassroom.stanford.edu/MainFolder/CoursePage.php? Course=machinelearning[2] Yu Zheng, L
experience is also a giant company such as Google fell a lot of holes summed up. It's not easy for us to be a giant.Next this article is now in the FB of the SGD Daniel Leon Bottou on icml to do on a tutorial. The title is: Two big challenges in machine learning, is a relatively biased system practice of the article, said is the two new challenges of the compute
First, MATLAB computer visioncontourlets-MATLAB source code for Contour Wave transformation and its use functionshearlets-MATLAB source code for Shear Wave transformationcurvelets-curvelet transformation of MATLAB source code (Curvelet transformation is to the higher dimension of the wavelet transform to the promotion of the different scales to represent the image)bandlets-bandlets transformation of MATLAB source codeNatural language ProcessingNLP-A NLP library of MATLABGeneral
Original: Image classification in 5 MethodsAuthor: Shiyu MouTranslation: He Bing Center
Image classification, as the name suggests, is an input image, output to the image content classification of the problem. It is the core of computer vision, which is widely used in practice.
The traditional method of image classification is feature description and detection, such traditional methods may be effective for some simple image classification, but the traditional classification method is overwhelmed
neighbor Category
Naive Bayesian algorithm
CART: Classification and regression tree algorithms
Ada Boost iterative algorithm
Support Vector Machine
Graph model
Clustering
K-mean-value clustering
Time series
Time Series Full Tutorial (R)
Hmm hidden Markov model
Dimension reduction
LDA Plain Unde
install Anacona. With Anaconda, you will be able to start using Python to explore the world of machine learning. The default installation library for Anaconda contains the tools needed for machine learning.Basic Machine learning SkillsWith some basic Python programming skil
Environment construction process is very troublesome ... But finally is ready, first give some of the process of reference to the more important information (find Microsoft's machine learning materials is a personal experience, without any reference):1. If the online various numpy, scipy and so on package installation tutorial trouble, go directly to: Microsoft
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