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Ploomber VS Scikit-learn

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

Ploomber logo Ploomber

Ploomber is an open-source framework that helps data scientists quickly deploy the code they develop in interactive environments (Jupyter, VScode, PyCharm, etc.), eliminating the need for time-consuming manual porting to production platforms.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Ploomber Landing page
    Landing page //
    2023-08-24
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Ploomber videos

Open-Source Spotlight - Ploomber - Eduardo Blancas

More videos:

  • Review - EDUARDO BLANCAS - Ploomber: Open-Source Tools for Maintainable and Production-Ready Data Science
  • Review - Ploomber: Developing Maintainable & Reproducible Data- Eduardo Blancas, Ido Michael | SciPy 2022

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 Ploomber and Scikit-learn)
AI
100 100%
0% 0
Data Science And Machine Learning
Developer 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 Ploomber and Scikit-learn

Ploomber 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 Ploomber. 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.

Ploomber mentions (7)

  • Show HN: JupySQL – a SQL client for Jupyter (ipython-SQL successor)
    - One-click sharing powered by Ploomber Cloud: https://ploomber.io Note that JupySQL is a fork of ipython-sql; which is no longer actively developed. Catherine, ipython-sql's creator, was kind enough to pass the project to us (check out ipython-sql's README). We'd love to learn what you think and what features we can ship for JupySQL to be the best SQL client! Please let us know in the comments! - Source: Hacker News / 6 months ago
  • A three-part series on deploying a Data Science Platform on AWS
    Developing end-to-end data science infrastructure can get complex. For example, many of us might have struggled to try to integrate AWS services and deal with configuration, permissions, etc. At Ploomber, we’ve worked with many companies in a wide range of industries, such as energy, entertainment, computational chemistry, and genomics, so we are constantly looking for simple solutions to get them started with... Source: over 1 year ago
  • Is Colab still the place to go?
    If you like working locally with notebooks, you can run via the free tier of ploomber, that'll allow you to get the Ram/Compute you need for the bigger models as part of the free tier. Also, it has the historical executions so you don't need to remember what you executed an hour later! Source: over 1 year ago
  • Saving log files
    That's what we do for lineage with https://ploomber.io/. Source: over 1 year ago
  • Three Tools for Executing Jupyter Notebooks
    NBClient supports running notebooks via CLI for the most basic use cases. However, for more sophisticated execution options, consider the Ploomber! - 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 / 3 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 / 12 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: about 1 year 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: over 1 year ago
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What are some alternatives?

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

Conduit - Your data-driven AI chief of staff

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

StorPool - StorPool is designed from the ground up to provide cloud builders, shared hosting providers and MSPs with the most resource efficient storage software on the market.

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

Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset

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