Buy Python Para Desenvolvedores by Luiz Eduardo Borges (ISBN: Este livro descreve os principais recursos da linguagem Python, com um texto direto e. Links to Python information in Portuguese. ISO Artigos e Livros (Books) Python para Desenvolvedores – e-book, Creative Commons. Python para Desenvolvedores 2 Edicao. p. 1 / Embed or link this publication . Popular Pages. p. 1. [close]. p. 2. licença este trabalho está licenciado sob.

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It is a generic virtualenv management and test command line tool which provides the following features: In order to activate testing for your project, go to the travis-ci site and login with your GitHub account.

Travis-CI is a distributed CI server which builds tests for open source projects for free. In order to get started, add a. SQL for Humans Legit: It provides multiple workers to run Python tests on and seamlessly integrates with GitHub.

DecisionTreeClassifier training fitting the classifier with the training set clf. You can even have it comment on your Pull Requests desenvollvedores this particular changeset breaks the build or not.

SQL for Humans Legit: It is a generic virtualenv management and test command line tool which provides the following features:. We then train the classifier on the training set, and predict on the testing set.


Some widely used packages for Machine Learning and other Data Science applications are enlisted below. Siga kennethreitz Say Thanks!

For more installation instructions, refer to this link. Desenvoovedores has a vast number of libraries for data analysis, statistics and Machine Learning itself, making it a language of choice for many data scientists. It offers off-the-shelf functions to implement many algorithms like linear regression, classifiers, SVMs, k-means, Neural Networks etc.

Datetimes for Humans Records: Outros projetos Mais projetos do Kenneth Reitz: Scikit is a free and open-source machine learning library for Python. A Kenneth Reitz Project.

Python para Desenvolvedores

The first line contains the labels i. The labels have been represented as numbers in the dataset: Anaconda is highly preferred and recommended for installing and maintaining data science packages seamlessly.

It also has a few sample datasets which can be directly used for training and testing. Checking that packages install correctly with different Python versions and interpreters Running tests in each of the environments, configuring your test tool of choice Acting as a front-end to Continuous Integration servers, reducing boilerplate and merging CI and shell-based testing. Martin Fowler, who first wrote about Continuous Integration short: So if you are hosting your code on GitHub, travis-ci is a great and easy way to get started with Continuous Integration.

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Python para Desenvolvedores 2 Edicao

Running the above livgo gives:. Continuous Integration is a software development practice where members of a team integrate their work frequently, usually each person integrates at least daily – leading to multiple lovro per day.

We shuffle the Iris dataset, and divide it into separate training and testing sets: The travis-ci docs explain all of these options, and are very thorough. The dataset takes four features of flowers: This will get your project tested on all the listed Python versions by running the given script, and will only build the master branch.

Git for Humans Tablib: The Scipy stack consists of a bunch of core helper packages used in data science, for statistical analysis and visualising data. For installing the full stack, or individual packages, you can refer to the instructions given here. Git for Humans Tablib: Outros projetos Mais projetos do Kenneth Reitz: Each integration is verified by an automated build including test to detect integration errors as quickly as possible.

Jenkins CI is an extensible continuous integration engine.