Software Alternatives, Accelerators & Startups

Buildbot VS Scikit-learn

Compare Buildbot VS Scikit-learn and see what are their differences

Buildbot logo Buildbot

Python-based continuous integration testing framework

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Buildbot Landing page
    Landing page //
    2021-09-21
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Buildbot videos

Craig Rodrigues - Migrating Python.org to Buildbot 9 and Python 3 - SF Python Meetup

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Buildbot and Scikit-learn)
Continuous Integration
100 100%
0% 0
Data Science And Machine Learning
DevOps Tools
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Buildbot and Scikit-learn

Buildbot Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Buildbot. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Buildbot mentions (9)

  • 10 open source tools that platform, SRE and DevOps engineers should consider in 2024.
    Buildbot is a versatile CI framework designed to automate all aspects of the software development cycle, enhancing efficiency and reliability. As an open-source platform, it is highly customizable, allowing teams to tailor the automation process to their specific needs. Buildbot excels in integrating various stages of development, from code integration, testing, to deployment, ensuring a seamless and coherent... - Source: dev.to / 4 months ago
  • Continuos Integration and C++
    If you want more than the builtin CIs in Github and Gitlab, https://buildbot.net is the way. Source: about 1 year ago
  • What are the open source CI/CD tools for C++ (comparable to Ansible, Jenkins, etc.)?
    If you don't have one already integrated with your source control, buildbot is pretty nice and doesn't force you to use docker like most others. Source: over 1 year ago
  • Why Jenkins?
    Https://buildbot.net/ existed before Jenkins Hudson and was quite well known. Source: over 1 year ago
  • Which is the best CI/CD self-hosted open source tool?
    I have used python based CI tool buildbot which is a great tool but we want to move away from buildbot only because in some scenarios we want to compile low-level microseconds which are in c++ to a different architecture. Buildbot doesn't have such a feature. - Source: dev.to / almost 2 years ago
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Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
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What are some alternatives?

When comparing Buildbot and Scikit-learn, you can also consider the following products

Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Travis CI - Focus on writing code. Let Travis CI take care of running your tests and deploying your apps.

OpenCV - OpenCV is the world's biggest computer vision library

CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.

NumPy - NumPy is the fundamental package for scientific computing with Python