Transferred from Infoq, author Zhang Tianrei
Machine learning is a hot topic in the field of data analysis, which often uses a variety of machine learning algorithms in peacetime learning and life. In fact, many of the machine
Example Response message: This section shows the JSON data format for the response message of the Web service, which includes the full JSON record (curly brace representation), the data table definition (datatabble), a series of columns in the datasheet (ColumnNames), The data type (columntypes) and the returned data values (values) for each column, where the fields in the data values list are separated by commas. An example of the response information returned from the API Web page.
and the platform also support Java,scala and Python bindings. This library is up-to-date and has many algorithms.
H2O is a machine learning API for smart applications. It has scaled statistics, machine learning, and mathematics on big data. H2O can be extended, and develope
is written in pure Java.
18. N-Dimensional Arrays for Java (ND4J) is a scientific computing library for JVM. They are used in the production environment, which indicates that the routine is designed to run with minimal memory requirements.
19. Java Machine Learning LibraryJava Machine Learning Library) is the implemen
that enables NLP.
Jsat is a library for quickly getting started with machine learning problems. It is developed in my free time, and made available for use under the GPL 3. Part of the library was for self education, as Such-all code was self contained. Jsat have no external dependencies, and is pure Java.
N-dimensional Arrays for Java (nd4j) are a scientific computing libraries for the JVM. They is me
A Gentle Introduction to the Gradient boosting algorithm for machine learning by Jason Brownlee on September 9 in xgboost 0000Gradient boosting is one of the most powerful techniques for building predictive models.In this post you'll discover the gradient boosting machine learning algorithm and get a gentle introdu
Setting up a deep learning machine from Scratch (software)A detailed guide-to-setting up your machine for deep learning. Includes instructions to the install drivers, tools and various deep learning frameworks. This is tested on a a-bit
Machine learning and Data Mining recommendation book listWith these books, no longer worry about the class no sister paper should do. Take your time, learn, and uncover the mystery of machine learning and data mining. machine learning
, rather than a mapping simplification). Although Java libraries and platforms support Java, Scala, and Python bindings. The library is new, the list of algorithms is short, but it grows fast. Moa
Large-scale online analysis (MOA) (Https://moa.cms waikato.ac.nz/) is an open source platform, designed by data stream mining at the University of New Zealand Waikato. Same as Weka (developed in the same place), providing a GUI, command-line interface, and J
examples.
Algorithms of the Intelligent Web (Smart Web algorithm) PDFAuthor Haralambos Marmanis, Dmitry Babenko. The formula in this book is a little bit more than "collective intelligence programming", the example of which is mostly the application on the Internet, to see the name. The disadvantage is that the matching code inside is BeanShell and not python or anything else. In general, this book is still suitable for beginners, and the same need
Learning notes of machine learning practice: Classification Method Based on Naive Bayes,
Probability is the basis of many machine learning algorithms. A small part of probability knowledge is used in the decision tree generation process, that is, to count the number of time
From Cold War to deep learning: An Illustrated History of machine translationSelected from vas3k.comIlya PestovEnglish Translator: Vasily ZubarevChinese Translator: Panda
The dream of high quality machine translation has been around for many years and many scientists have contributed their time and effort to this dream. From early rule-based
say we have some data points, and now we use a straight line to fit these points, so that this line represents the distribution of data points as much as possible, and this fitting process is called regression.In machine learning tasks, the training of classifiers is the process of finding the best fit curve, so the optimization algorithm will be used next. Before implementing the algorithm, summarize some
attention.Deep Learning (learning) is a new field in ML research that is introduced into ML to bring ml closer to its original target: AI. View a brief introduction to machine learning for AI and an introduction to deep learning algorithms.Deep
Learning notes of machine learning practice: Implementation of decision trees,
Decision tree is an extremely easy-to-understand algorithm and the most commonly used data mining algorithm. It allows machines to create rules based on datasets. This is actually the process of machine
https://zhuanlan.zhihu.com/p/21276788ObjectiveOriginally this title I think is the skill of algorithmic engineer, but I think if add machine learning in the title, the estimated point of people will be more, so the title into this, hehe, and is indexed by the search engine when more a popular word, estimated exposure will be more points. But rest assured, the article is not tricky, we are serious. Today tal
Spark. Although it is Java, the library and platform also support binding Java, Scala and Python. This library is up-to-date and has many algorithms.
22. H2O is a machine learning API for smart applications. It scales statistics, machine learning, and mathematics on big dat
This is a creation in
Article, where the information may have evolved or changed.
Golang
The following are all derived from Studygolang (known by the General People):
The "the" to Go Chinese-no-smell translation
https://gobyexample.com/
50 Go developers often make mistakes (English)
relative to "Golang language programming" is more suitable for beginners to get started.
"Golang language Programming" Xu Xiwei
more comprehensive explanation of Golang, there are project examples, with other lan
data in fr.readlines ()] Lenseslabel = [ ' age ' , ' prescript ' , ' astigmatic ' , ' tearrate ' ]lensestree = Tree.buildtree ( Lensesdata, Lenseslabel) #print lensesdata print lensestreeprint plottree.createplot (lensestree) It can be seen that the early implementation of the decision tree construction and drawing, using different data sets can be very intuitive results, you can see, along the different branches of the decision tree, you can get different patients need to wear the ty
New Smart Dollar recommendations Source: LinkedIn Abhishek Thakur Translator: Ferguson "New wisdom meta-reading" This is a popular Kaggle article published by data scientist Abhishek Thakur. The author summed up his experience in more than 100 machine learning competitions, mainly from the model framework to explain the machine
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