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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SQL for Humans Legit: Outros projetos Mais projetos do Kenneth Reitz: Anaconda is highly preferred and recommended for installing and maintaining data science packages seamlessly.

Some widely used packages for Machine Learning and other Data Science applications are enlisted below.

The Scipy stack consists of a bunch of core helper packages used in data science, for statistical analysis and visualising data. It provides multiple workers to run Python tests on and seamlessly integrates with GitHub.

Git for Humans Tablib: Datetimes for Humans Records: Siga kennethreitz Say Thanks! For this example, we train apra simple classifier on the Iris datasetwhich comes bundled in with scikit-learn. A Kenneth Reitz Project.

Python para Desenvolvedores

It is a generic virtualenv management and test command line tool which provides the pyhon features:. The dataset takes four features of flowers: 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 Desenvolvedorez and shell-based testing.


DecisionTreeClassifier training fitting the classifier with the training set clf. Because of its huge number of functionalities and ease of use, the Stack is considered a must-have for most data science applications.

Integração contínua — O Guia do Mochileiro para Python

There are a lot more options you can enable, like notifications, before and after steps and much more. Datetimes for Humans Records: A Kenneth Reitz Project. It is a generic virtualenv management and test command line tool which provides the following features: More on scikit-learn can be read in the documentation.

It also has a few sample datasets which can be directly used for training and testing. For installing the full stack, or individual packages, you can refer to the instructions given here. The labels have been represented as numbers in the dataset: So if you are hosting your code on GitHub, travis-ci is a great and easy way to get started with Continuous Integration.

Python para Desenvolvedores 2 Edicao

Git for Humans Tablib: Scikit is a free and open-source machine learning library for Python. We shuffle the Iris dataset, and divide it into separate training and testing sets: The Stack consists of the following packages link to documentation given: SQL for Humans Legit: For more installation instructions, refer to this link.

Jenkins CI is an extensible desnvolvedores integration engine. It offers off-the-shelf functions to implement many algorithms like linear regression, classifiers, SVMs, k-means, Neural Networks etc. Siga kennethreitz Say Thanks! Martin Fowler, who first wrote about Continuous Integration short: Running the above code desenvolvvedores. Python has a vast number of libraries for data analysis, statistics and Machine Learning itself, making it a language of choice for many data scientists.


Travis-CI is a distributed CI server which builds tests for open source projects for free. In order to activate testing for your project, go to the travis-ci site and login with your GitHub account. We then train the classifier on the training set, and predict on the testing set. This will get your project tested on all the listed Python versions by running the given script, and will only build the master branch.

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. The travis-ci docs explain all of these options, and are very thorough.

You can even have it comment on your Pull Requests whether this particular changeset breaks the build or not. Many teams find that this approach leads to significantly reduced integration problems and allows a team to develop cohesive software more rapidly.

O Guia do Mochileiro para Python! — O Guia do Mochileiro para Python

The first line contains the labels i. In order to get started, add a. 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 integrations per day.