udacity python machine learning

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11 Open source projects for machine learning

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

Getting Started with Azure machine learning (iv) model Publishing as a Web service

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.

25 Java machine learning tools and libraries

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

25 Java machine learning tools and libraries

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

Java machine learning Tools & libraries--Reprint

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

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)

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 list

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

Super full! Java-based machine learning project, environment, library ... __java

, 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

Machine Learning Classic books [Turn]

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,

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 translation

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

Learning in the field of machine learning notes: Logistic regression & predicting mortality of hernia disease syndrome

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

Neural network and support vector machine for deep learning

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,

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

What skills/Algorithmic engineers are required for machine learning

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

25 Java machine learning tools and libraries

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

2015 Learning Recommended Books (Golang, Web, machine learning)

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

Machine learning in Action Learning notes: Drawing a tree chart & predicting contact lens types using decision Trees

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

Dry Kaggle Popular | Solve all machine learning challenges with a single framework

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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